Query Classification based Information Retrieval System

被引：0

作者：

Khin, Naw Thiri Wai ^{[1
]}

Yee, Nyo Nyo ^{[1
]}

机构：

[1] Univ Technol Yatanarpon Cyber City, Fac Informat & Commun Technol, Pyin Oo Lwin, Myanmar

来源：

2018 INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATICS AND BIOMEDICAL SCIENCES (ICIIBMS) | 2018年

关键词：

query; domain term extraction; query classification algorithm; NoSQL database; IR;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Information Retrieval (IR) system finds the relevant documents from a large dataset according to the user query. Queries submitted by users to search engines might be ambiguous, concise and their meaning may change over time. As a result, understanding the nature of information that is needed behind the queries has become an important research problem. So, various search engines emphasize the web query classification. For the efficient IR system, this system proposes the Web Query Classification Algorithm (WQCA) by using NoSQL graph database. This system classifies the web queries into each characteristic and each predefined target categories. In web query classification, the input query is first classified into web search taxonomies (characteristics). Then, domain terms are extracted from the query, and each of them is classified into their relevant categories that are stored in the NoSQL database. By using categories from WQCA, this system finds the relevant document from the document collection. The vector space IR model is used in this system to retrieve the relevant document.

引用

页码：151 / 156

页数：6

共 50 条

[31] Predicting Query Quality for Applications of Text Retrieval to Software Engineering Tasks [J].

Mills, Chris ;

Bavota, Gabriele ;

Haiduc, Sonia ;

Oliveto, Rocco ;

Marcus, Andrian ;

De Lucia, Andrea .

ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY, 2017, 26 (01)

[32] Research on classification query optimization algorithm in data stream [J].

Zhou Hong ;

Wang Bin ;

Fu Chunyan ;

Zhi Yuan ;

Xue Jiamei .

PROCEEDINGS OF THE 2015 2ND INTERNATIONAL CONFERENCE ON ELECTRICAL, COMPUTER ENGINEERING AND ELECTRONICS (ICECEE 2015), 2015, 24 :1219-1223

[33] An ontology-based retrieval system using semantic indexing [J].

Kara, Soner ;

Alan, Ozgur ;

Sabuncu, Orkunt ;

Akpinar, Samet ;

Cicekli, Nihan K. ;

Alpaslan, Ferda N. .

INFORMATION SYSTEMS, 2012, 37 (04) :294-305

[34] Scalable Hypergraph-based Image Retrieval and Tagging System [J].

Chen, Lu ;

Gao, Yunjun ;

Zhang, Yuanliang ;

Wang, Sibo ;

Zheng, Baihua .

2018 IEEE 34TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE), 2018, :257-268

[35] A similarity query system for road traffic data based on a NoSQL document store [J].

Damaiyanti, Titus Irma ;

Imawan, Ardi ;

Indikawati, Fitri Indra ;

Choi, Yoon-Ho ;

Kwon, Joonho .

JOURNAL OF SYSTEMS AND SOFTWARE, 2017, 127 :28-51

[36] Semantic Tourism Information Retrieval Interface [J].

Laddha, Shilpa S. ;

Jawandhiya, Pradip M. .

2017 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI), 2017, :694-697

[37] Query-driven indexing for scalable peer-to-peer text retrieval [J].

Skobeltsyn, Gleb ;

Luu, Toan ;

Zarko, Ivana Podnar ;

Rajman, Martin ;

Aberer, Karl .

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2009, 25 (01) :89-99

[38] Intelligent query refine and expansion model for the retrieval of E-learning resources [J].

Chellatamilan, T. ;

Suresh, R.M. .

Chellatamilan, T., 1600, Asian Network for Scientific Information (13) :485-490

[39] Genetic-based approaches in ranking function discovery and optimization in information retrieval - A framework [J].

Fan, Weiguo ;

Pathak, Praveen ;

Zhou, Mi .

DECISION SUPPORT SYSTEMS, 2009, 47 (04) :398-407

[40] Feature string-based intelligent information retrieval from Tamil document images [J].

Abirami, S. ;

Manjula, D. .

INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY, 2009, 35 (2-4) :150-164

← 1 2 3 4 5 →