All Outputs (2)

A bipartite graph-based ranking approach to query subtopics diversification focused on word embedding features (2016)
Journal Article
Ullah, M. Z., & Aono, M. (2016). A bipartite graph-based ranking approach to query subtopics diversification focused on word embedding features. IEICE Transactions on Information and Systems, 99(12), 3090-3100. https://doi.org/10.1587/transinf.2016EDP7190

Web search queries are usually vague, ambiguous, or tend to have multiple intents. Users have different search intents while issuing the same query. Understanding the intents through mining subtopics underlying a query has gained much interest in rec... Read More about A bipartite graph-based ranking approach to query subtopics diversification focused on word embedding features.

Query Subtopic Mining Exploiting Word Embedding for Search Result Diversification (2016)
Presentation / Conference Contribution
Ullah, M. Z., Chy, A. N., & Aono, M. (2016). Query Subtopic Mining Exploiting Word Embedding for Search Result Diversification. In Information Retrieval Technology: 12th Asia Information Retrieval Societies Conference, AIRS 2016, Beijing, China, Novembe

Understanding the users’ search intents through mining query subtopic is a challenging task and a prerequisite step for search diversification. This paper proposes mining query subtopic by exploiting the word embedding and short-text similarity measu... Read More about Query Subtopic Mining Exploiting Word Embedding for Search Result Diversification.