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Abstract

Information retrieval process is an inference for the real-world user communication, which is based on the concept of storing, representing and searching information. Moreover, it utilizes the repository in order to retrieve the stored information in an effective way. The processing of such system is not an easy task; also, its complexity depends on the quality of searched information. The information that would be retrieved depends on the query formed by the user. The fuzziness of human brain is extremely high as every person has different cognitive skills, opinions, thinking, perception, situation, intention, intuition and domain; these varied attributes results in a fuzzy query by the user for any information need, thus it can be said that different types of user have different query apprehension. In order to provide efficient and relevant results to the user according to the information need, the foremost requirement is to understand the users’ query. In this paper, hybrid of Vector Space Model with fuzzy logic inference has been implemented. The purpose of the system is mapping of the Vector Space Model with cognitive skills of the user using the fuzzy approach. The similarity between the documents has been computed using the fuzzy logic in order to evaluate the query results based on the graininess of the user.

Keywords

Information Retrieval cognitive vector space fuzzy logic terrier TREC hybrid

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References

Chawla

. Application of hybrid of fuzzy set, trust and genetic algorithm in query log mining for effective information retrieval. International Journal of Intelligent Systems and Applications in Engineering. 2018; 6(1): 47-52.

Khezri

Hosseini

Mazinani

. A fuzzy rule-based expert system for the prognosis of the risk of development of the breast cancer. 2014.

Chiew

Lau

. Monotonicity preserving SIRMs-connected fuzzy inference system for predicting HPC compressive strength. Intelligent Decision Technologies. 2018; 1-10.

Kanagavalli

Raja

. A fuzzy logic based method for efficient retrieval of vague and uncertain spatial expressions in text exploiting the granulation of the spatial event queries. in: International Journal of Computer Applications (0975-8887), National Conference on Future Computing CoRR. 2013.

Wilson

Devillers

Hoeber

. Fuzzy logic ranking for personalized geographic information retrieval. in: Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011). Prague, Czech Republic, August, 2011. Springer, Berlin, Heidelberg. 2013; 111-123.

Jakhar

Rajnish

. MEasurement of complexity and comprehension of a program through a cognitive approach. International Journal of Engineering-Transactions B: Applications. 2015; 28(11): 1579.

Abualigah

Khader

Hanandeh

. A hybrid strategy for krill herd algorithm with harmony search algorithm to improve the data clustering. Intelligent Decision Technologies. 2018; 1-12.

Mahdizadeh

Eftekhari

. Proposing a novel cost sensitive imbalanced classification method based on hybrid of new fuzzy cost assigning approaches, fuzzy clustering and evolutionary algorithms. International Journal of Engineering-Transactions B: Applications. 2015; 28(8): 1160.

http://trec.nist.gov/data/topics_eng/index.html.

10.

http://trec.nist.gov/data/qrels_eng/index.html.

11.

www.terrier.org.

12.

Jayashree

Devi

Papandrianos

Papageorgiou

. Application of fuzzy cognitive map for geospatial dengue outbreak risk prediction of tropical regions of Southern India. Intelligent Decision Technologies. 2018; 1-20.

13.

Chawla

. Effective personalization of web search based on fuzzy information retrieval. International Journal of Computer Science and Information Technologies. 2015; 6(3): 2831-2837.

14.

Beigbeder

Mercier

. An information retrieval model using the fuzzy proximity degree of term occurences. in: Proceedings of the 2005 ACM Symposium on Applied Computing. ACM. 2005 March; 1018-1022.

15.

Rubens

. The application of fuzzy logic to the construction of the ranking function of information retrieval systems. arXiv preprint cs/0610039. 2006.

16.

Gupta

Saini

Saxena

. A new fuzzy logic based ranking function for efficient information retrieval system. Expert Systems with Applications. 2015; 42(3): 1223-1234.

17.

Beigbeder

Mercier

. An information retrieval model using the fuzzy proximity degree of term occurences. 2005.

18.

Schwarzer

Schubotz

Meuschke

Breitinger

Markl

Gipp

. Evaluating link-based recommendations for Wikipedia. in: Digital Libraries (JCDL), 2016 IEEE/ACM Joint Conference on. IEEE. 2016 June; 191-200.

19.

Kasemsap

. Mastering web mining and information retrieval in the digital age. Web usage mining techniques and applications across industries. 2017; 1-28.

20.

Hannah

Geetha

Mukherjee

. Automatic extractive text summarization based on fuzzy logic: A sentence oriented approach. in: International Conference on Swarm, Evolutionary, and Memetic Computing. Springer, Berlin, Heidelberg. 2011 December; 530-538.

21.

Doran

Yetilmezsoy

Murtazaoglu

. Application of fuzzy logic approach in predicting the lateral confinement coefficient for RC columns wrapped with CFRP. Engineering Structures. 2015; 88: 74-91.

22.

Sanchiz

Chevalier

Amadieu

. How do older and young adults start searching for information? Impact of age, domain knowledge and problem complexity on the different steps of information searching. Computers in Human Behavior. 2017; 72: 67-78.

23.

Dewan

Biswas

. A unified approach for fuzzy multiobjective stochastic programming with Cauchy and extreme value distributed fuzzy random variables. Intelligent Decision Technologies. 2018; 1-11.

24.

Roy

Kumar

Sharma

. A novel fuzzy document based information retrieval model for forecasting. Fuzzy Information and Engineering. 2017; 9(2): 137-159.

25.

Roelleke

. Information retrieval models: Foundations and relationships. Synthesis Lectures on Information Concepts, Retrieval, and Services. 2013; 5(3): 1-163.

Mapping of the vector space model with cognitive skills of the user using fuzzy approach

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