Query expansion for document retrieval based on fuzzy rules and user relevance feedback techniques

2006 ◽  
Vol 31 (2) ◽  
pp. 397-405 ◽  
Author(s):  
Hsi-Ching Lin ◽  
Li-Hui Wang ◽  
Shyi-Ming Chen
2012 ◽  
Vol 30 (3) ◽  
pp. 523-544 ◽  
Author(s):  
Dan Wu ◽  
Daqing He ◽  
Xiaomei Xu

PurposeWith the vast amount of multilingual information available online, it becomes increasingly critical for libraries to use various multilingual information access techniques in order to effectively support patrons' online information requests. However, this is still a relatively under‐explored area. This paper aims to study the effectiveness and the adoptability of query expansion and translation enhancement in the context of interactive multilingual information access.Design/methodology/approachRelying on an interactive multilingual information access system called ICE‐TEA, the authors conducted a controlled experiment (English‐to‐Chinese translation) involving human subjects to assess the retrieval effectiveness, analyzed the collected search logs to examine users' behavior, and employed pre‐ and post‐questionnaires to obtain users' opinions about the system.FindingsThe results confirm that significant improvement in retrieval effectiveness can be achieved by combining query expansion with translation enhancement (as compared to a case when there is no relevance feedback). However, users' ability to understand, interact with and even perceive the complex process of searches involving the combination of query expansion and translation enhancement may greatly impact the effectiveness of the techniques. The results also confirm that human‐generated queries were short queries, which calls for careful consideration of how longer queries perform in real search because many search engines rely on longer and more complex queries.Originality/valueThis study examines two important relevance feedback techniques in the context of human‐involved multilingual information access. This study is a valuable addition to the information seeking behaviour literature.


2014 ◽  
Vol 28 (4) ◽  
pp. 344-359 ◽  
Author(s):  
Gyeong June Hahm ◽  
Mun Yong Yi ◽  
Jae Hyun Lee ◽  
Hyo Won Suh

2008 ◽  
Author(s):  
Makoto Terao ◽  
Takafumi Koshinaka ◽  
Shinichi Ando ◽  
Ryosuke Isotani ◽  
Akitoshi Okumura

2015 ◽  
Vol 5 (4) ◽  
pp. 31-45 ◽  
Author(s):  
Jagendra Singh ◽  
Aditi Sharan

Pseudo-relevance feedback (PRF) is a type of relevance feedback approach of query expansion that considers the top ranked retrieved documents as relevance feedback. In this paper the authors focus is to capture the limitation of co-occurrence and PRF based query expansion approach and the authors proposed a hybrid method to improve the performance of PRF based query expansion by combining query term co-occurrence and query terms contextual information based on corpus of top retrieved feedback documents in first pass. Firstly, the paper suggests top retrieved feedback documents based query term co-occurrence approach to select an optimal combination of query terms from a pool of terms obtained using PRF based query expansion. Second, contextual window based approach is used to select the query context related terms from top feedback documents. Third, comparisons were made among baseline, co-occurrence and contextual window based approaches using different performance evaluating metrics. The experiments were performed on benchmark data and the results show significant improvement over baseline approach.


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