Study of Query Expansion Techniques and Their Application in the Biomedical Information Retrieval

Rivas, Aurea; Iglesias, Eva; Borrajo, Lourdes

doi:10.1155/2014/132158

Cited by 36 publications

(18 citation statements)

References 25 publications

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“…Since our work considers open government data with potential geospatial terms, another knowledge base (ConceptNet) was considered as an alternative. Despite the difficulty of using concepts as query expansion terms, ConceptNet has been evaluated for query expansion by [2,6,24,25,55]. We take a deeper look at both knowledge bases in the next subsections.…”

Section: Query Expansionmentioning

confidence: 99%

Spatial search strategies for open government data

Degbelo

Teka

2019

Proceedings of the 13th Workshop on Geographic Information Retrieval

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The increasing availability of open government datasets on the Web calls for ways to enable their efficient access and searching. There is however an overall lack of understanding regarding spatial search strategies which would perform best in this context. To address this gap, this work has assessed the impact of different spatial search strategies on performance and user relevance judgment. We harvested machine-readable spatial datasets and their metadata from three English-based open government data portals, performed metadata enhancement, developed a prototype and performed both a theoretical and user-based evaluation. The results highlight that (i) switching between area of overlap and Hausdorff distance for spatial similarity computation does not have any substantial impact on performance; and (ii) the use of Hausdorff distance induces slightly better user relevance ratings than the use of area of overlap. The data collected and the insights gleaned may serve as a baseline against which future work can compare.

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Section: Query Expansionmentioning

confidence: 99%

Spatial search strategies for open government data

Degbelo

Teka

2019

Proceedings of the 13th Workshop on Geographic Information Retrieval

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“…It expands the query with the top relevant documents terms that re-weights by sum weights of that term in all top relevant documents. Rivas and other are well known to enhance the performance of the IR using Rocchio's with the biomedical dataset [37]. The limitation of this approach is the term weight that reflects the significance of that term to the entire collection instead of its usefulness to the user query.…”

Section: B Automatic Query Expansion Approachesmentioning

confidence: 99%

A Novel Information Retrieval Approach using Query Expansion and Spectral-based

Alnofaie¹,

Dahab²,

Kamal³

2016

ijacsa

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Abstract-Most of the information retrieval (IR) models rank the documents by computing a score using only the lexicographical query terms or frequency information of the query terms in the document. These models have a limitation as they does not consider the terms proximity in the document or the term-mismatch or both of the two. The terms proximity information is an important factor that determines the relatedness of the document to the query. The ranking functions of the Spectral-Based Information Retrieval Model (SBIRM) consider the query terms frequency and proximity in the document by comparing the signals of the query terms in the spectral domain instead of the spatial domain using Discrete Wavelet Transform (DWT). The query expansion (QE) approaches are used to overcome the word-mismatch problem by adding terms to query, which have related meaning with the query. The QE approaches are divided to statistical approach Kullback-Leibler divergence (KLD) and semantic approach P-WNET that uses WordNet. These approaches enhance the performance. Based on the foregoing considerations, the objective of this research is to build an efficient QESBIRM that combines QE and proximity SBIRM by implementing the SBIRM using the DWT and KLD or P-WNET. The experiments conducted to test and evaluate the QESBIRM using Text Retrieval Conference (TREC) dataset. The result shows that the SBIRM with the KLD or P-WNET model outperform the SBIRM model in precision (P@), R-precision, Geometric Mean Average Precision (GMAP) and Mean Average Precision (MAP).

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“…It renovates the original query by updating the query keywords or their weights to enhance efficiency of information retrieval [11]. According to different sources of the new keywords, available techniques in query expansion can be divided into two classes: global and local analysis [12,13]. Global analysis utilizes external corpus or thesaurus, a vocabulary recording terms, and their relationships.…”

Section: Introductionmentioning

confidence: 99%

Collecting Typhoon Disaster Information from Twitter Based on Query Expansion

Chen¹,

Lim²

2018

IJGI

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Social media is a popular source of volunteered geographic information owing to its massive real-time data; however, the use of social media data in the context of geospatial analysis is challenging because complex semantic filters are required for the aggregation of geographic messages from the data streams. This article proposes a new query expansion method for social media streams which updates the query keywords periodically by the words extracted from the preceding search results. The proposed method has optimized the trade-off between precision and coverage of geographical messages by factoring in the influences of the keyword number and refresh cycle in the query process, and some improvements on the classic Term Frequency-Inverse Document Frequency (TF-IDF) method for short texts were achieved. Furthermore, a number of filters based upon relevance to the target topic were established and tested. This method was tested on a dataset from Twitter within the geographic extent of Macau in August 2017 during two consecutive typhoon hits. The result supports its effectiveness with a controllable precision and considerable increment of relevant information. Moreover, the query keywords can adjust themselves to the local language environment by discovering new keywords. To conclude, this query expansion method is able to provide a reliable method for social media-based information retrieval.

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Study of Query Expansion Techniques and Their Application in the Biomedical Information Retrieval

Cited by 36 publications

References 25 publications

Spatial search strategies for open government data

Spatial search strategies for open government data

A Novel Information Retrieval Approach using Query Expansion and Spectral-based

Collecting Typhoon Disaster Information from Twitter Based on Query Expansion

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