Multi-grained Document Modeling for Search Result Diversification
Article No.: 126, Pages 1 - 22
Abstract
Search result diversification plays a crucial role in improving users’ search experience by providing users with documents covering more subtopics. Previous studies have made great progress in leveraging inter-document interactions to measure the similarity among documents. However, different parts of the document may embody different subtopics and existing models ignore the subtle similarities and differences of content within each document. In this article, we propose a hierarchical attention framework to combine intra-document interactions with inter-document interactions in a complementary manner in order to conduct multi-grained document modeling. Specifically, we separate the document into passages to model the document content from multi-grained perspectives. Then, we design stacked interaction blocks to conduct inter-document and intra-document interactions. Moreover, to measure the subtopic coverage of each document more accurately, we propose a passage-aware document-subtopic interaction to perform fine-grained document-subtopic interaction. Experimental results demonstrate that our model achieves state-of-the-art performance compared with existing methods.
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Index Terms
- Multi-grained Document Modeling for Search Result Diversification
Recommendations
Passage-aware Search Result Diversification
Research on search result diversification strives to enhance the variety of subtopics within the list of search results. Existing studies usually treat a document as a whole and represent it with one fixed-length vector. However, considering that a long ...
Term level search result diversification
SIGIR '13: Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrievalCurrent approaches for search result diversification have been categorized as either implicit or explicit. The implicit approach assumes each document represents its own topic, and promotes diversity by selecting documents for different topics based on ...
Modeling Intent Graph for Search Result Diversification
SIGIR '21: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information RetrievalSearch result diversification aims to offer diverse documents that cover as many intents as possible. Most existing implicit diversification approaches model diversity through the similarity of document representation, which is indirect and unnatural. To ...
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Publication History
Published: 27 April 2024
Online AM: 15 March 2024
Accepted: 06 March 2024
Revised: 03 January 2024
Received: 08 November 2022
Published in TOIS Volume 42, Issue 5
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- National Natural Science Foundation of China
- Renmin University of China
- Public Computing Cloud, Renmin University of China
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