Details
| Original language | English |
|---|---|
| Title of host publication | The Semantic Web - 15th International Conference, ESWC 2018, Proceedings |
| Editors | Aldo Gangemi, Raphaël Troncy, Roberto Navigli, Laura Hollink, Maria-Esther Vidal, Pascal Hitzler, Anna Tordai, Mehwish Alam |
| Publisher | Springer Verlag |
| Pages | 462-480 |
| Number of pages | 19 |
| ISBN (print) | 9783319934167 |
| Publication status | Published - 3 Jun 2018 |
| Event | 15th International Conference on Extended Semantic Web Conference, ESWC 2018 - Heraklion, Greece Duration: 3 Jun 2018 → 7 Jun 2018 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 10843 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
Entity aspect recommendation is an emerging task in semantic search that helps users discover serendipitous and prominent information with respect to an entity, of which salience (e.g., popularity) is the most important factor in previous work. However, entity aspects are temporally dynamic and often driven by events happening over time. For such cases, aspect suggestion based solely on salience features can give unsatisfactory results, for two reasons. First, salience is often accumulated over a long time period and does not account for recency. Second, many aspects related to an event entity are strongly time-dependent. In this paper, we study the task of temporal aspect recommendation for a given entity, which aims at recommending the most relevant aspects and takes into account time in order to improve search experience. We propose a novel event-centric ensemble ranking method that learns from multiple time and type-dependent models and dynamically trades off salience and recency characteristics. Through extensive experiments on real-world query logs, we demonstrate that our method is robust and achieves better effectiveness than competitive baselines.
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
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The Semantic Web - 15th International Conference, ESWC 2018, Proceedings. ed. / Aldo Gangemi; Raphaël Troncy; Roberto Navigli; Laura Hollink; Maria-Esther Vidal; Pascal Hitzler; Anna Tordai; Mehwish Alam. Springer Verlag, 2018. p. 462-480 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10843 LNCS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Multiple Models for Recommending Temporal Aspects of Entities
AU - Nguyen, Tu Ngoc
AU - Kanhabua, Nattiya
AU - Nejdl, Wolfgang
N1 - Funding information: This work was partially funded by the German Federal Ministry of Education and Research (BMBF) under project GlycoRec (16SV7172). Acknowledgements. This work was partially funded by the German Federal Ministry of Education and Research (BMBF) under project GlycoRec (16SV7172).
PY - 2018/6/3
Y1 - 2018/6/3
N2 - Entity aspect recommendation is an emerging task in semantic search that helps users discover serendipitous and prominent information with respect to an entity, of which salience (e.g., popularity) is the most important factor in previous work. However, entity aspects are temporally dynamic and often driven by events happening over time. For such cases, aspect suggestion based solely on salience features can give unsatisfactory results, for two reasons. First, salience is often accumulated over a long time period and does not account for recency. Second, many aspects related to an event entity are strongly time-dependent. In this paper, we study the task of temporal aspect recommendation for a given entity, which aims at recommending the most relevant aspects and takes into account time in order to improve search experience. We propose a novel event-centric ensemble ranking method that learns from multiple time and type-dependent models and dynamically trades off salience and recency characteristics. Through extensive experiments on real-world query logs, we demonstrate that our method is robust and achieves better effectiveness than competitive baselines.
AB - Entity aspect recommendation is an emerging task in semantic search that helps users discover serendipitous and prominent information with respect to an entity, of which salience (e.g., popularity) is the most important factor in previous work. However, entity aspects are temporally dynamic and often driven by events happening over time. For such cases, aspect suggestion based solely on salience features can give unsatisfactory results, for two reasons. First, salience is often accumulated over a long time period and does not account for recency. Second, many aspects related to an event entity are strongly time-dependent. In this paper, we study the task of temporal aspect recommendation for a given entity, which aims at recommending the most relevant aspects and takes into account time in order to improve search experience. We propose a novel event-centric ensemble ranking method that learns from multiple time and type-dependent models and dynamically trades off salience and recency characteristics. Through extensive experiments on real-world query logs, we demonstrate that our method is robust and achieves better effectiveness than competitive baselines.
UR - http://www.scopus.com/inward/record.url?scp=85048516806&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-93417-4_30
DO - 10.1007/978-3-319-93417-4_30
M3 - Conference contribution
AN - SCOPUS:85048516806
SN - 9783319934167
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 462
EP - 480
BT - The Semantic Web - 15th International Conference, ESWC 2018, Proceedings
A2 - Gangemi, Aldo
A2 - Troncy, Raphaël
A2 - Navigli, Roberto
A2 - Hollink, Laura
A2 - Vidal, Maria-Esther
A2 - Hitzler, Pascal
A2 - Tordai, Anna
A2 - Alam, Mehwish
PB - Springer Verlag
T2 - 15th International Conference on Extended Semantic Web Conference, ESWC 2018
Y2 - 3 June 2018 through 7 June 2018
ER -