query recommendation
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2021 ◽  
Vol 18 (8) ◽  
pp. 169-182
Author(s):  
Jin Xie ◽  
Fuxi Zhu ◽  
Huanmei Guan ◽  
Jiangqing Wang ◽  
Hao Feng ◽  
...  

2020 ◽  
Vol 23 (2) ◽  
pp. 523-535 ◽  
Author(s):  
Debaditya Barman ◽  
Ritam Sarkar ◽  
Anil Tudu ◽  
Nirmalya Chowdhury

2020 ◽  
Vol 17 (1) ◽  
pp. 445-450
Author(s):  
Chetana Badgujar ◽  
Vimla Jethani ◽  
Tushar Ghorpade

Exploratory search aids in the production of desired results which improve browsing abilities of user in current era. To improve search engine performance, this method inspects search goal shift to obtain pertinent knowledge about query entered by the user. The existing system fails to provide bigram relationship and ignores synonyms of the submitted query. Also there is un-certainty of spam links which may be included in the final result. To overcome these lacunas, the proposed framework will conduct an exploratory search to recommend query by making use of bi-gram approach which will also remove the spam links with the help of trust rank algorithm and finds all possible synonyms of the submitted query in order to obtain a proper result. This phenomenon helps to produce better user recommendations.


2019 ◽  
Vol 8 (3) ◽  
pp. 3755-3760

Semantic search plays a vital role for improving the output of information retrieval in today’s scenario. Users those who want to find the necessary information always feel comfortable to submit queries based on related keywords to the search engine. But, the major drawback of submitting keyword query is ambiguity. So, we are moving to semantic based search. Many traditional approaches like semantic search depending on ontology encourages user to type a formal language query. Most of the novice users are not aware of formal query languages. To resolve the above drawback and enhance the retrieval effectiveness, a semantic based recommendation tool using domain specific ontology is proposed. And also to solve the limitations of usability, a query interface has to be provided to the users in which the users can enter the natural language query. To implement this semantic based recommendation tool, a domain-specific ontology is used through which accurate search results can be achieved. This Query Recommendation tool is proposed for Library Management System which uses Library Ontology for Query Recommendation. This tool compares the input query given by the user related to Library with the Library ontology and other possible queries which are related to the user query are generated from the ontology based on different entities and relationship. The queries which are extracted from the ontology using entities and properties along with query log are recommended alternative to the user’s initial query. Since, the queries are extracted based on the semantics by which the concepts related to the user query are revealed, more relevant information is retrieved which leads to user satisfaction


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