Keyword search in information retrieval and relational database system: Two class view

Pawar, Sanket Sunil; Manepatil, Abhijeet; Kadam, Aniket; Jagtap, Prajakta

doi:10.1109/iceeot.2016.7755576

Cited by 6 publications

(4 citation statements)

References 9 publications

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“…In the information retrieval field, keyword query has become a prevalent and mature query technology [1][2][3]. Users are only required to submit a list of keywords to the query system and then they can get the desired information easily.…”

Section: Introductionmentioning

confidence: 99%

A Two-phase Ranking Method for the Relational Databases

Wang¹,

Zhou²,

Wang³

2019

International Journal of Computational Linguistics Research

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With the extensive application of keyword query in relational database, the ranking algorithm has become an important research topic. Most existing ranking methods have adopted IR-style ranking models without considering the effects of semantic relevancy and diversity on the ranking results. In this paper, we propose a novel ranking method on the basis of semantic relevancy and diversity. First, we define the concepts of basic semantics and complex semantics and then add them to the ranking function. Next, aiming at the generation of redundancy, we design the diversity strategy to re-rank query results. Experimental results demonstrate that our method has better performance in terms of precision and recall.

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Section: Introductionmentioning

confidence: 99%

A Two-phase Ranking Method for the Relational Databases

Wang¹,

Zhou²,

Wang³

2019

International Journal of Computational Linguistics Research

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“…In information retrieval, the keyword query method has been widely applied according to its simplicity and ease of use [7,15,19]. In recent years, it has been introduced into the relational database and become mature [11,16].…”

Section: Introductionmentioning

confidence: 99%

Keyword Query based on Hypergraph in Relational Database

Wang¹

2018

IJPE

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Recently, the keyword query in relational databases has received widespread attention. The traditional methods typically traverse the entire database for the final results. With the database, structure becomes more complex and its size increases quickly; the efficiency of above methods cannot be ensured. To solve this issue, we propose a hypergraph-based keyword query method. First, the concept of hypergraph is formally defined to model the relational database. Second, the strategy of multi-granular index construction is presented to prune the irrelevant supernodes. Then, a filtering-validating query method is put forward based on the above index. Finally, experiments are taken on the dataset DBLP to verify the validity of the proposed method.

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“…An answer for this Web data recovery issue is the information disclosure in the outcomes that normal information retrieval system give. Separating knowledge [2] and gathering the outcomes returned by a web information retrieval into a progression of marked clusters (additionally called classifications), is a critical undertaking that cutting-edge web information retrievals as of late began thinking about by giving subject clustered outcomes, the client may center on a general point by entering a nonexclusive inquiry, and after that select these topics that match his advantage. Clustering [3] information retrieval systems can be valuable as they give quicker point recovery following the topical gathering as opposed to perusing the entire rundown of the outcomes.…”

Section: Introductionmentioning

confidence: 99%

“…It is observed that certain like word replacement, acronym growth and spell check, and find dissimilar are other to source clicks, in particular on high ranked based results. In [2], it is declared that about 28% of roughly 2 billion daily web based information retrieval changes to be depend upon on previous query. In [3], proposed the Dogpile.com logs, to description that 37% of seeks queries are reformulations when overlook the similar queries.…”

Section: Introductionmentioning

confidence: 99%

Semantic Sense Annotation from User Query by using Web Search Techniques

Mahajan¹,

Vijay²

2018

ICST Transactions on Ubiquitous Environments

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These days, individuals as often as possible use search engines keeping in mind the end goal to discover the information they must on the web. Be that as it may, as a rule, web information retrieval appear rear to most often searched web pages in a worldwide positioning makes difficulties to the clients to pursue distinctive themes fixed the outcome set and in this way making it tough to discover rapidly the coveted webpages. The requirements for uncommon calculation process of the frameworks that will discover knowledge in this web-based searching comes about giving the client the likelihood to pursue diverse themes controlled to given outcome set. The proposed model consists of phases, primarily used to reduce execution time in URL fetch. The first phase includes preprocessing that handle the error in words of the input query, the second phase is a unique keyword segmentation that extracts synonyms corresponding keywords. The keywords segmentation process is used most probable clustering mechanism to reduce overall execution time by grouping the similar keywords so that server doesn't involve again and again, the third phase includes the sense segmentation. This phase fetches the URL corresponding to synonyms fetched in the second phase. In the results section, the results in terms of execution time indicate improvement by and a number of a fetched result.

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Keyword search in information retrieval and relational database system: Two class view

Cited by 6 publications

References 9 publications

A Two-phase Ranking Method for the Relational Databases

A Two-phase Ranking Method for the Relational Databases

Keyword Query based on Hypergraph in Relational Database

Semantic Sense Annotation from User Query by using Web Search Techniques

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