Enhancing Web Search through Query Expansion

2011 ◽  
pp. 752-757 ◽  
Author(s):  
Daniel Crabtree
Keyword(s):  
Information Retrieval ◽  
Search Engines ◽  
Query Expansion ◽  
Web Search ◽  
User Involvement ◽  
Semantic Knowledge ◽  
Web Pages ◽  
Search Performance ◽  
Interactive Query ◽  
Web Search Engines

Web search engines help users find relevant web pages by returning a result set containing the pages that best match the user’s query. When the identified pages have low relevance, the query must be refined to capture the search goal more effectively. However, finding appropriate refinement terms is difficult and time consuming for users, so researchers developed query expansion approaches to identify refinement terms automatically. There are two broad approaches to query expansion, automatic query expansion (AQE) and interactive query expansion (IQE) (Ruthven et al., 2003). AQE has no user involvement, which is simpler for the user, but limits its performance. IQE has user involvement, which is more complex for the user, but means it can tackle more problems such as ambiguous queries. Searches fail by finding too many irrelevant pages (low precision) or by finding too few relevant pages (low recall). AQE has a long history in the field of information retrieval, where the focus has been on improving recall (Velez et al., 1997). Unfortunately, AQE often decreased precision as the terms used to expand a query often changed the query’s meaning (Croft and Harper (1979) identified this effect and named it query drift). The problem is that users typically consider just the first few results (Jansen et al., 2005), which makes precision vital to web search performance. In contrast, IQE has historically balanced precision and recall, leading to an earlier uptake within web search. However, like AQE, the precision of IQE approaches needs improvement. Most recently, approaches have started to improve precision by incorporating semantic knowledge.

The potential and actual effectiveness of interactive query expansion

1997 ◽  
Vol 31 (SI) ◽  
pp. 324-332 ◽  
Author(s):  
Mark Magennis ◽  
Cornelis J. van Rijsbergen
Keyword(s):  
Query Expansion ◽  
Interactive Query ◽  
Actual Effectiveness

The Use of Arabic WordNet in Arabic Information Retrieval

2014 ◽  
Vol 4 (3) ◽  
pp. 54-65 ◽  
Author(s):  
Ahmed Abbache ◽  
Fatiha Barigou ◽  
Fatma Zohra Belkredim ◽  
Ghalem Belalem
Keyword(s):  
Information Retrieval ◽  
Query Expansion ◽  
Appropriate Use ◽  
Average Precision ◽  
Linguistic Information ◽  
Interactive Query ◽  
Part Of Speech ◽  
Arabic Information Retrieval ◽  
Princeton Wordnet ◽  
The Impact

Research and experimentation using Arabic WordNet in the field of information retrieval are relatively new. It is limited compared to the research that has been done using Princeton WordNet. This work attempts to study the impact of Arabic WordNet on the performance of Arabic information retrieval. We extend Lucene with Arabic WordNet to expand user's queries. The major contribution of this study is to propose an interactive query expansion (IQE) methodology using the word's part-of-speech, according to the part it plays in a query. First, the user selects the appropriate part of speech for each term in the original query, and then he reselects the appropriate synonyms. Experimental results show that our IQE strategy produces a good Mean Average Precision (MAP), it is able to improve MAP by 12.6%, but no variant of automatic query expansion (AQE) strategies did. Nevertheless, the experiments allow us to conclude that with an appropriate use of Arabic WordNet as a source of linguistic information for AQE can improve effectiveness for Arabic information retrieval.

Interactive Query Expansion with Automatically Generated Category-Specific Thesauri

2011 ◽  
pp. 103-117
Author(s):  
Fabrizio Sebastiani
Keyword(s):  
Information Retrieval ◽  
Search Engines ◽  
Information Seeking ◽  
Query Expansion ◽  
Document Collections ◽  
Web Based ◽  
Interactive Query ◽  
Retrieval Systems ◽  
Subject Specific ◽  
Information Retrieval Systems

The categorization of documents into subject-specific categories is a useful enhancement for large document collections addressed by information retrieval systems, as a user can first browse a category tree in search of the category that best matches her interests and then issue a query for more specific documents “from within the category.” This approach combines two modalities in information seeking that are most popular in Web-based search engines, i.e., category-based site browsing (as exemplified by, e.g., Yahoo™) and keyword-based document querying (as exemplified by, e.g., AltaVista™). Appropriate query expansion tools need to be provided, though, in order to allow the user to incrementally refine her query through further retrieval passes, thus allowing the system to produce a series of subsequent document rankings that hopefully converge to the user’s expected ranking. In this work we propose that automatically generated, category-specific “associative” thesauri be used for such purpose. We discuss a method for their generation and discuss how the thesaurus specific to a given category may usefully be endowed with “gateways” to the thesauri specific to its parent and children categories.

Query Reformulation Behavior in an Interactive Query Expansion Environment

2011 ◽  
Vol 11 (3) ◽  
pp. 161-172
Author(s):  
Carola Carstens ◽  
Dorothea Mildner
Keyword(s):  
Query Expansion ◽  
Query Reformulation ◽  
Interactive Query
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