@inproceedings{7182d37f38574403b03619d92245820d,
title = "Context-aware entity summarization",
abstract = "Entity summarization aims at selecting a small subset of attribute-value pairs of an entity from a knowledge graph, which provides users with concrete information given an entity-related query. However, previous approaches focus on the “goodness” of the attribute-value pairs, paying little attention to user preference towards them. In this paper, we formalize the task of context-aware entity summarization, and propose an algorithm to solve this problem. We model user interest by mining the latent topics in a query log dataset. A modified Personalized PageRank algorithm is utilized to rank attribute-value pairs by leveraging three elements: relevance, informativeness and topic coherence. We evaluate our approach on real-world datasets and show that it outperforms the state-of-the-art approaches.",
keywords = "Entity summarization, Personalized Page Rank, Query log, Topic model",
author = "Jihong Yan and Yanhua Wang and Ming Gao and Aoying Zhou",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 17th International Conference on Web-Age Information Management, WAIM 2016 ; Conference date: 03-06-2016 Through 05-06-2016",
year = "2016",
doi = "10.1007/978-3-319-39937-9\_40",
language = "英语",
isbn = "9783319399362",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "517--529",
editor = "Jianliang Xu and Nan Zhang and Dexi Liu and Bin Cui and Xiang Lian",
booktitle = "Web-Age Information Management - 17th International Conference, WAIM 2016, Proceedings",
address = "德国",
}