A personalized query expansion approach for engineering document retrieval

Hahm, Gyeong June; Yi, Mun Yong; Lee, Jae Hyun; Suh, Hyo Won

doi:10.1016/j.aei.2014.04.002

Cited by 38 publications

(26 citation statements)

References 27 publications

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“…Semantic query expansion methods may differ in semantic supporter and semantic expansion strategy. Many studies utilize ontology to express semantic relation and implement semantic query expansion on ontology [5][6][7]. M. Shabanzadeh et al extracted semantically related words from WordNet [5].…”

Section: Related Workmentioning

confidence: 99%

“…It is often to expand the user query with the new terms that meaning are closely related to the input keywords. Such relationships are usually extracted from large scale thesauri or semantic supporter, such as WordNet, domain ontology, linked data [5][6][7][8] and semantic expansion strategy [9][10][11][12][13][14][15], in which various sets of synonyms, hyponyms, etc. are often predefined.…”

Section: Introductionmentioning

confidence: 99%

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Personalized Semantic Query Expansion Based on Dynamic User Query Profile and Spreading Activation Model

Zhu¹,

Meng²,

Chen³

et al. 2017

IJHIT

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show abstract

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Personalized Semantic Query Expansion Based on Dynamic User Query Profile and Spreading Activation Model

Zhu¹,

Meng²,

Chen³

et al. 2017

IJHIT

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show abstract

“…Such short queries lack of words that if were provided, could be very useful search terms [7]. The QE goal is to add new meaningful terms to the initial query [8]. For example, for a query stating Pilas which is an ambiguous plural-form Spanish word that may refer to batteries, cells, heaps and stacks, adding the word Baterias (batteries) to the query would be meaningful because it would help the system to identify the domain the user is trying to query about.…”

Section: B Query Expansionmentioning

confidence: 99%

An Information Retrieval Model using Query Expansion based on Ontologies in the Computer Science Domain

Chávez¹,

Melgar

2015

International Conferences on Software Engineering and Knowledge Engineering

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Abstract-This paper presents a model that aims to support knowledge retrieval stored in digital repositories through domain ontologies. In this model the ontology contains concepts and relationships which describe a specific part of the world. The model mechanisms aim to reduce the impact of some of the main obstacles identified in the Information Retrieval process such as user specific characteristics, natural language characteristics or retrieval systems limitations. As a result the user, by providing a query to the system, can retrieve relevant information which better meet his information need. A prototype was developed to demonstrate the feasibility of the model using queries in the computer science domain.

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“…In [16] Lee et al proposed a method in which documents are ranked by using domain ontology and user's profile. User's interests are captured and the query is expanded based on that.…”

Section: Query Expansion Based On Term Weighingmentioning

confidence: 99%

A Comprehensive Survey on Query Expansion Techniques, their Issues and Challenges

Kathuria¹,

Mittal²,

Chhabra³

2017

IJCA

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In order to improve the retrieval performance, the process of Query expansion is performed on the original user's query in order to reformulate the user's query. The basis of these query expansion techniques is to expand the query by adding the terms, which are in close proximity to the original query terms. Various query expansion techniques do not consider the context of the terms present in the user's query which can result in low precision and recall due to the ambiguity and vagueness of terms present in the query. Through this paper, a comprehensive survey is presented to study the various query expansion techniques proposed in literature by researchers and the various keyholes in the current scenario.

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A personalized query expansion approach for engineering document retrieval

Cited by 38 publications

References 27 publications

Personalized Semantic Query Expansion Based on Dynamic User Query Profile and Spreading Activation Model

Personalized Semantic Query Expansion Based on Dynamic User Query Profile and Spreading Activation Model

An Information Retrieval Model using Query Expansion based on Ontologies in the Computer Science Domain

A Comprehensive Survey on Query Expansion Techniques, their Issues and Challenges

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