ON AN INTERPRETATION OF KEYWORDS WEIGHTS IN INFORMATION RETRIEVAL: SOME FUZZY LOGIC BASED APPROACHES

2009 ◽  
Vol 17 (supp01) ◽  
pp. 41-58 ◽  
Author(s):  
SŁAWOMIR ZADROŻNY ◽  
JANUSZ KACPRZYK
Keyword(s):  
Fuzzy Logic ◽  
Information Retrieval ◽  
Boolean Model ◽  
Retrieval Process ◽  
Retrieval Models ◽  
Logical Approach ◽  
Logical Models

Relevant contributions of fuzzy logic to the logical models in information retrieval is studied. It makes it possible to grasp the graduality of some relevant concepts and to model both imprecision and uncertainty inherent to the retrieval process, still in the framework of the broadly meant logical approach. In this perspective we discuss various extensions to the basic Boolean model which are needed to attain such a greater expressivity. In particular, we show how the well-known semantics of keywords weights may be recovered in various fuzzy logic based information retrieval models.

Semantic / Fuzzy Information Retrieval System

2017 ◽  
Vol 12 (1) ◽  
pp. 37-56
Author(s):  
Mounira Chkiwa ◽  
Anis Jedidi ◽  
Faiez Gargouri
Keyword(s):  
Fuzzy Logic ◽  
Information Retrieval ◽  
Semantic Web ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Retrieval Process ◽  
Fuzzy Information ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Fuzzy Information Retrieval

In this paper, the authors present an overall description of their information retrieval system which makes a practical collaboration between Semantic Web and Fuzzy logic in order to have profit from their advantages in the information retrieval domain. Their system is dedicated for kids, for this reason the semantic/fuzzy collaboration materialized must be in the background of the information retrieval process because such category of users cannot certainly control semantic web technologies neither fuzzy logic commands. In this paper, the authors present the different services proposed by their system and how they use Semantic Web and Fuzzy logic to develop it. Evaluation tests of the system using universal measures show clearly its efficiency.

Information Retrieval in Virtual Universities

2008 ◽  
pp. 555-566
Author(s):  
Juha Puustjarvi ◽  
Pa¨ivi Poyry
Keyword(s):  
Information Retrieval ◽  
Search Engine ◽  
Boolean Model ◽  
Learning Objects ◽  
Learning Object ◽  
Vector Model ◽  
Easy Access ◽  
Retrieval Models ◽  
Web Searches ◽  
Virtual Universities

Information retrieval in the context of virtual universities deals with the representation, organization and access to learning objects. The representation and organization of learning objects should provide the learner with an easy access to the learning objects. In this paper, we give an overview of the ONES system and analyze the relevance of two information retrieval models for virtual universities. We argue that keywords-based search (i.e., the Boolean model), though well suited for Web searches, is overly coarse for virtual universities. Instead, the vector model, on which our implemented search engine also is based, seems to be more appropriate, as it provides similarity measure (i.e., the learning object having the best match is presented first). We also compare the performance of four algorithms for computing the similarities (matching).

Semantic/Fuzzy Information Retrieval System

2018 ◽  
pp. 1030-1050
Author(s):  
Mounira Chkiwa ◽  
Anis Jedidi ◽  
Faiez Gargouri
Keyword(s):  
Fuzzy Logic ◽  
Information Retrieval ◽  
Semantic Web ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Retrieval Process ◽  
Fuzzy Information ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Fuzzy Information Retrieval

In this paper, the authors present an overall description of their information retrieval system which makes a practical collaboration between Semantic Web and Fuzzy logic in order to have profit from their advantages in the information retrieval domain. Their system is dedicated for kids, for this reason the semantic/fuzzy collaboration materialized must be in the background of the information retrieval process because such category of users cannot certainly control semantic web technologies neither fuzzy logic commands. In this paper, the authors present the different services proposed by their system and how they use Semantic Web and Fuzzy logic to develop it. Evaluation tests of the system using universal measures show clearly its efficiency.

Information Retrieval in Virtual Universities

2011 ◽  
pp. 1676-1688
Author(s):  
Juha Puustjarvi ◽  
Päivi Poyry
Keyword(s):  
Information Retrieval ◽  
Search Engine ◽  
Boolean Model ◽  
Learning Objects ◽  
Learning Object ◽  
Vector Model ◽  
Easy Access ◽  
Retrieval Models ◽  
Web Searches ◽  
Virtual Universities

Information retrieval in the context of virtual universities deals with the representation, organization, and access to learning objects. The representation and organization of learning objects should provide the learner with an easy access to the learning objects. In this article, we give an overview of the ONES system, and analyze the relevance of two information retrieval models for virtual universities. We argue that keywords based search (i.e., the Boolean model), though well suited for Web searches, is overly coarse for virtual universities. Instead, the vector model, on which our implemented search engine is also based on, seems to be more appropriate as it provides similarity measure (i.e., the learning object having the best match is presented first). We also compare the performance of four algorithms for computing the similarities (matching).

Information Retrieval in Virtual Universities

2011 ◽  
pp. 194-206
Author(s):  
Juha Puustjärvi ◽  
Päivi Pöyry
Keyword(s):  
Information Retrieval ◽  
Search Engine ◽  
Boolean Model ◽  
Learning Objects ◽  
Learning Object ◽  
Vector Model ◽  
Easy Access ◽  
Retrieval Models ◽  
Web Searches ◽  
Virtual Universities

Information retrieval in the context of virtual universities deals with the representation, organization, and access to learning objects. The representation and organization of learning objects should provide the learner with an easy access to the learning objects. In this chapter, we give an overview of the ONES system, and analyze the relevance of two information retrieval models for virtual universities. We argue that keywords based search (i.e., the Boolean model), though well suited for Web searches, is overly coarse for virtual universities. Instead, the vector model, on which our implemented search engine is also based on, seems to be more appropriate as it provides similarity measure (i.e., the learning object having the best match is presented first). We also compare the performance of four algorithms for computing the similarities (matching).

A Survey on Information Retrieval Models, Techniques and Applications

2017 ◽  
Vol 7 (7) ◽  
pp. 16 ◽  
Author(s):  
Ndengabaganizi Tonny James ◽  
Rajkumar Kannan
Keyword(s):  
Information Retrieval ◽  
Retrieval Models ◽  
Knowledge Based ◽  
Long Time

It has been long time many people have realized the importance of archiving and finding information. With the advent of computers, it became possible to store large amounts of information; and finding useful information from such collections became a necessity. Over the last forty years, Information Retrieval (IR) has matured considerably. Several IR systems are used on an everyday basis by a wide variety of users. Information retrieval (IR) is generally concerned with the searching and retrieving of knowledge-based information from database. In this paper, we will discuss about the various models and techniques and for information retrieval. We are also providing the overview of traditional IR models.

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