Generating Recommendation Evidence Using Translation Model
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 2810-2815.
Abstract
Entity recommendation, providing entity suggestions relevant to the query that a user is searching for, has become a key feature of today's web search engine. Despite the fact that related entities are relevant to users' search queries, sometimes users cannot easily understand the recommended entities without evidences. This paper proposes a statistical model consisting of four sub-models to generate evidences for entities, which can help users better understand each recommended entity, and figure out the connections between the recommended entities and a given query. The experiments show that our method is domain independent, and can generate catchy and interesting evidences in the application of entity recommendation.
@inproceedings{ijcai2016p399,
title = {Generating Recommendation Evidence Using Translation Model},
author = {Huang, Jizhou and Zhao, Shiqi and Ding, Shiqiang and Wu, Haiyang and Sun, Mingming and Wang, Haifeng},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {2810--2815},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/399},
}
TY - CPAPER TI - Generating Recommendation Evidence Using Translation Model AU - Huang, Jizhou AU - Zhao, Shiqi AU - Ding, Shiqiang AU - Wu, Haiyang AU - Sun, Mingming AU - Wang, Haifeng T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 2810 EP - 2815 UR - https://ijcai.org/proceedings/2016/399 ER -Copied
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