NDLI: Leveraging integrated information to extract query subtopics for search result diversification

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Leveraging integrated information to extract query subtopics for search result diversification

Content Provider	Springer Nature Link
Author	Zheng, Wei Fang, Hui Yao, Conglei Wang, Min
Copyright Year	2013
Abstract	Search result diversification aims to diversify search results to cover different query subtopics, i.e., pieces of relevant information. The state of the art diversification methods often explicitly model the diversity based on query subtopics, and their performance is closely related to the quality of subtopics. Most existing studies extracted query subtopics only from the unstructured data such as document collections. However, there exists a huge amount of information from structured data, which complements the information from the unstructured data. The structured data can provide valuable information about domain knowledge, but is currently under-utilized. In this article, we study how to leverage the integrated information from both structured and unstructured data to extract high quality subtopics for search result diversification. We first discuss how to extract subtopics from structured data. We then propose three methods to integrate structured and unstructured data. Specifically, the first method uses the structured data to guide the subtopic extraction from unstructured data, the second one uses the unstructured data to guide the extraction, and the last one first extracts the subtopics separately from two data sources and then combines those subtopics. Experimental results in both Enterprise and Web search domains show that the proposed methods are effective in extracting high quality subtopics from the integrated information, which can lead to better diversification performance.
Starting Page	52
Ending Page	73
Page Count	22
File Format	PDF
ISSN	13864564
Journal	Information Retrieval
Volume Number	17
Issue Number	1
e-ISSN	15737659
Language	English
Publisher	Springer Netherlands
Publisher Date	2013-07-04
Publisher Place	Dordrecht
Access Restriction	Subscribed
Subject Keyword	Web search Enterprise search Diversification Query subtopics Structured data Unstructured data Information Storage and Retrieval Document Preparation and Text Processing Data Mining and Knowledge Discovery Data Structures, Cryptology and Information Theory Pattern Recognition
Content Type	Text
Resource Type	Article
Subject	Library and Information Sciences Information Systems

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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