Personalized user engagement modeling for mobile videos
The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video se...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Yang, Lin [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2017transfer abstract |
|---|
| Umfang: |
12 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls - Poo, J.L. ELSEVIER, 2016, the international journal of computer and telecommunications networking, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:126 ; year:2017 ; day:24 ; month:10 ; pages:256-267 ; extent:12 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.comnet.2017.07.012 |
|---|
| Katalog-ID: |
ELV040264599 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | ELV040264599 | ||
| 003 | DE-627 | ||
| 005 | 20230625231342.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 180603s2017 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.comnet.2017.07.012 |2 doi | |
| 028 | 5 | 2 | |a GBV00000000000383.pica |
| 035 | |a (DE-627)ELV040264599 | ||
| 035 | |a (ELSEVIER)S1389-1286(17)30293-1 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 610 |q VZ |
| 082 | 0 | 4 | |a 610 |q VZ |
| 084 | |a 44.44 |2 bkl | ||
| 100 | 1 | |a Yang, Lin |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Personalized user engagement modeling for mobile videos |
| 264 | 1 | |c 2017transfer abstract | |
| 300 | |a 12 | ||
| 336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
| 337 | |a nicht spezifiziert |b z |2 rdamedia | ||
| 338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
| 520 | |a The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain. | ||
| 520 | |a The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain. | ||
| 700 | 1 | |a Yuan, Mingxuan |4 oth | |
| 700 | 1 | |a Chen, Yanjiao |4 oth | |
| 700 | 1 | |a Wang, Wei |4 oth | |
| 700 | 1 | |a Zhang, Qian |4 oth | |
| 700 | 1 | |a Zeng, Jia |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier |a Poo, J.L. ELSEVIER |t Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls |d 2016 |d the international journal of computer and telecommunications networking |g Amsterdam [u.a.] |w (DE-627)ELV013796984 |
| 773 | 1 | 8 | |g volume:126 |g year:2017 |g day:24 |g month:10 |g pages:256-267 |g extent:12 |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.comnet.2017.07.012 |3 Volltext |
| 912 | |a GBV_USEFLAG_U | ||
| 912 | |a GBV_ELV | ||
| 912 | |a SYSFLAG_U | ||
| 912 | |a SSG-OLC-PHA | ||
| 912 | |a GBV_ILN_40 | ||
| 936 | b | k | |a 44.44 |j Parasitologie |x Medizin |q VZ |
| 951 | |a AR | ||
| 952 | |d 126 |j 2017 |b 24 |c 1024 |h 256-267 |g 12 | ||
| author_variant |
l y ly |
|---|---|
| matchkey_str |
yanglinyuanmingxuanchenyanjiaowangweizha:2017----:esnlzdsrnaeetoeigo |
| hierarchy_sort_str |
2017transfer abstract |
| bklnumber |
44.44 |
| publishDate |
2017 |
| allfields |
10.1016/j.comnet.2017.07.012 doi GBV00000000000383.pica (DE-627)ELV040264599 (ELSEVIER)S1389-1286(17)30293-1 DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.44 bkl Yang, Lin verfasserin aut Personalized user engagement modeling for mobile videos 2017transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain. The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain. Yuan, Mingxuan oth Chen, Yanjiao oth Wang, Wei oth Zhang, Qian oth Zeng, Jia oth Enthalten in Elsevier Poo, J.L. ELSEVIER Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls 2016 the international journal of computer and telecommunications networking Amsterdam [u.a.] (DE-627)ELV013796984 volume:126 year:2017 day:24 month:10 pages:256-267 extent:12 https://doi.org/10.1016/j.comnet.2017.07.012 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 44.44 Parasitologie Medizin VZ AR 126 2017 24 1024 256-267 12 |
| spelling |
10.1016/j.comnet.2017.07.012 doi GBV00000000000383.pica (DE-627)ELV040264599 (ELSEVIER)S1389-1286(17)30293-1 DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.44 bkl Yang, Lin verfasserin aut Personalized user engagement modeling for mobile videos 2017transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain. The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain. Yuan, Mingxuan oth Chen, Yanjiao oth Wang, Wei oth Zhang, Qian oth Zeng, Jia oth Enthalten in Elsevier Poo, J.L. ELSEVIER Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls 2016 the international journal of computer and telecommunications networking Amsterdam [u.a.] (DE-627)ELV013796984 volume:126 year:2017 day:24 month:10 pages:256-267 extent:12 https://doi.org/10.1016/j.comnet.2017.07.012 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 44.44 Parasitologie Medizin VZ AR 126 2017 24 1024 256-267 12 |
| allfields_unstemmed |
10.1016/j.comnet.2017.07.012 doi GBV00000000000383.pica (DE-627)ELV040264599 (ELSEVIER)S1389-1286(17)30293-1 DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.44 bkl Yang, Lin verfasserin aut Personalized user engagement modeling for mobile videos 2017transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain. The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain. Yuan, Mingxuan oth Chen, Yanjiao oth Wang, Wei oth Zhang, Qian oth Zeng, Jia oth Enthalten in Elsevier Poo, J.L. ELSEVIER Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls 2016 the international journal of computer and telecommunications networking Amsterdam [u.a.] (DE-627)ELV013796984 volume:126 year:2017 day:24 month:10 pages:256-267 extent:12 https://doi.org/10.1016/j.comnet.2017.07.012 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 44.44 Parasitologie Medizin VZ AR 126 2017 24 1024 256-267 12 |
| allfieldsGer |
10.1016/j.comnet.2017.07.012 doi GBV00000000000383.pica (DE-627)ELV040264599 (ELSEVIER)S1389-1286(17)30293-1 DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.44 bkl Yang, Lin verfasserin aut Personalized user engagement modeling for mobile videos 2017transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain. The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain. Yuan, Mingxuan oth Chen, Yanjiao oth Wang, Wei oth Zhang, Qian oth Zeng, Jia oth Enthalten in Elsevier Poo, J.L. ELSEVIER Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls 2016 the international journal of computer and telecommunications networking Amsterdam [u.a.] (DE-627)ELV013796984 volume:126 year:2017 day:24 month:10 pages:256-267 extent:12 https://doi.org/10.1016/j.comnet.2017.07.012 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 44.44 Parasitologie Medizin VZ AR 126 2017 24 1024 256-267 12 |
| allfieldsSound |
10.1016/j.comnet.2017.07.012 doi GBV00000000000383.pica (DE-627)ELV040264599 (ELSEVIER)S1389-1286(17)30293-1 DE-627 ger DE-627 rakwb eng 610 VZ 610 VZ 44.44 bkl Yang, Lin verfasserin aut Personalized user engagement modeling for mobile videos 2017transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain. The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain. Yuan, Mingxuan oth Chen, Yanjiao oth Wang, Wei oth Zhang, Qian oth Zeng, Jia oth Enthalten in Elsevier Poo, J.L. ELSEVIER Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls 2016 the international journal of computer and telecommunications networking Amsterdam [u.a.] (DE-627)ELV013796984 volume:126 year:2017 day:24 month:10 pages:256-267 extent:12 https://doi.org/10.1016/j.comnet.2017.07.012 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 44.44 Parasitologie Medizin VZ AR 126 2017 24 1024 256-267 12 |
| language |
English |
| source |
Enthalten in Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls Amsterdam [u.a.] volume:126 year:2017 day:24 month:10 pages:256-267 extent:12 |
| sourceStr |
Enthalten in Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls Amsterdam [u.a.] volume:126 year:2017 day:24 month:10 pages:256-267 extent:12 |
| format_phy_str_mv |
Article |
| bklname |
Parasitologie |
| institution |
findex.gbv.de |
| dewey-raw |
610 |
| isfreeaccess_bool |
false |
| container_title |
Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls |
| authorswithroles_txt_mv |
Yang, Lin @@aut@@ Yuan, Mingxuan @@oth@@ Chen, Yanjiao @@oth@@ Wang, Wei @@oth@@ Zhang, Qian @@oth@@ Zeng, Jia @@oth@@ |
| publishDateDaySort_date |
2017-01-24T00:00:00Z |
| hierarchy_top_id |
ELV013796984 |
| dewey-sort |
3610 |
| id |
ELV040264599 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV040264599</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230625231342.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180603s2017 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.comnet.2017.07.012</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBV00000000000383.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV040264599</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S1389-1286(17)30293-1</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.44</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Yang, Lin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Personalized user engagement modeling for mobile videos</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2017transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">12</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yuan, Mingxuan</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chen, Yanjiao</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Wei</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhang, Qian</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zeng, Jia</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Poo, J.L. ELSEVIER</subfield><subfield code="t">Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls</subfield><subfield code="d">2016</subfield><subfield code="d">the international journal of computer and telecommunications networking</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV013796984</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:126</subfield><subfield code="g">year:2017</subfield><subfield code="g">day:24</subfield><subfield code="g">month:10</subfield><subfield code="g">pages:256-267</subfield><subfield code="g">extent:12</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.comnet.2017.07.012</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">44.44</subfield><subfield code="j">Parasitologie</subfield><subfield code="x">Medizin</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">126</subfield><subfield code="j">2017</subfield><subfield code="b">24</subfield><subfield code="c">1024</subfield><subfield code="h">256-267</subfield><subfield code="g">12</subfield></datafield></record></collection>
|
| author |
Yang, Lin |
| spellingShingle |
Yang, Lin ddc 610 bkl 44.44 Personalized user engagement modeling for mobile videos |
| authorStr |
Yang, Lin |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV013796984 |
| format |
electronic Article |
| dewey-ones |
610 - Medicine & health |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
elsevier |
| remote_str |
true |
| illustrated |
Not Illustrated |
| topic_title |
610 VZ 44.44 bkl Personalized user engagement modeling for mobile videos |
| topic |
ddc 610 bkl 44.44 |
| topic_unstemmed |
ddc 610 bkl 44.44 |
| topic_browse |
ddc 610 bkl 44.44 |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
zu |
| author2_variant |
m y my y c yc w w ww q z qz j z jz |
| hierarchy_parent_title |
Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls |
| hierarchy_parent_id |
ELV013796984 |
| dewey-tens |
610 - Medicine & health |
| hierarchy_top_title |
Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)ELV013796984 |
| title |
Personalized user engagement modeling for mobile videos |
| ctrlnum |
(DE-627)ELV040264599 (ELSEVIER)S1389-1286(17)30293-1 |
| title_full |
Personalized user engagement modeling for mobile videos |
| author_sort |
Yang, Lin |
| journal |
Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls |
| journalStr |
Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
600 - Technology |
| recordtype |
marc |
| publishDateSort |
2017 |
| contenttype_str_mv |
zzz |
| container_start_page |
256 |
| author_browse |
Yang, Lin |
| container_volume |
126 |
| physical |
12 |
| class |
610 VZ 44.44 bkl |
| format_se |
Elektronische Aufsätze |
| author-letter |
Yang, Lin |
| doi_str_mv |
10.1016/j.comnet.2017.07.012 |
| dewey-full |
610 |
| title_sort |
personalized user engagement modeling for mobile videos |
| title_auth |
Personalized user engagement modeling for mobile videos |
| abstract |
The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain. |
| abstractGer |
The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain. |
| abstract_unstemmed |
The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain. |
| collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_40 |
| title_short |
Personalized user engagement modeling for mobile videos |
| url |
https://doi.org/10.1016/j.comnet.2017.07.012 |
| remote_bool |
true |
| author2 |
Yuan, Mingxuan Chen, Yanjiao Wang, Wei Zhang, Qian Zeng, Jia |
| author2Str |
Yuan, Mingxuan Chen, Yanjiao Wang, Wei Zhang, Qian Zeng, Jia |
| ppnlink |
ELV013796984 |
| mediatype_str_mv |
z |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth oth oth oth oth |
| doi_str |
10.1016/j.comnet.2017.07.012 |
| up_date |
2024-07-06T17:03:23.018Z |
| _version_ |
1803849986757099520 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV040264599</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230625231342.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180603s2017 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.comnet.2017.07.012</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBV00000000000383.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV040264599</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S1389-1286(17)30293-1</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.44</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Yang, Lin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Personalized user engagement modeling for mobile videos</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2017transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">12</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The ever-increasing mobile video services and users’ demand for better video quality have boosted research into the video Quality-of-Experience. Recently, the concept of Quality-of-Experience has evolved to Quality-of-Engagement, a more actionable metric to evaluate users’ engagement to the video services and directly relate to the service providers’ revenue model. Existing works on user engagement mostly adopt uniform models to quantify the engagement level of all users, overlooking the essential distinction of individual users. In this paper, we first conduct a large-scale measurement study on a real-world data set to demonstrate the dramatic discrepancy in user engagement, which implies that a uniform model is not expressive enough to characterize the distinctive engagement pattern of each user. To address this problem, we propose PE, a personalized user engagement model for mobile videos, which, for the first time, addresses the user diversity in the engagement modeling. Evaluation results on a real-world data set show that our system significantly outperforms the uniform engagement models, with a 19.14% performance gain.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yuan, Mingxuan</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chen, Yanjiao</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Wei</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhang, Qian</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zeng, Jia</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Poo, J.L. ELSEVIER</subfield><subfield code="t">Pharmacokinetics of the Antifibrotic Drug Pirfenidone in Child Pugh A and B Cirrhotic Patients Compared to Healthy Age-Matched Controls</subfield><subfield code="d">2016</subfield><subfield code="d">the international journal of computer and telecommunications networking</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV013796984</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:126</subfield><subfield code="g">year:2017</subfield><subfield code="g">day:24</subfield><subfield code="g">month:10</subfield><subfield code="g">pages:256-267</subfield><subfield code="g">extent:12</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.comnet.2017.07.012</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">44.44</subfield><subfield code="j">Parasitologie</subfield><subfield code="x">Medizin</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">126</subfield><subfield code="j">2017</subfield><subfield code="b">24</subfield><subfield code="c">1024</subfield><subfield code="h">256-267</subfield><subfield code="g">12</subfield></datafield></record></collection>
|
| score |
7.3989973 |