A Study on Models and Methods of Information Retrieval System

2018 ◽  
pp. 246-265
Author(s):  
Manisha Malhotra ◽  
Aarti Singh
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Information Resources ◽  
Retrieval Process ◽  
Database Query ◽  
Text Indexing ◽  
Unique Result ◽  
The Given

Information Retrieval (IR) is the action of getting the information applicable to a data need from a pool of information resources. Searching can be depends on text indexing. Whenever a client enters an inquiry into the system, an automated information retrieval process becomes starts. Inquiries are formal statements which is required for getting an input (Rijsbergen, 1997). It is not necessary that the given query provides the relevance information. That query matches the result of required information from the database. It doesn't mean it gives the precise and unique result likewise in SQL queries (Rocchio, 2010). Its results are based on the ranking of information retrieved from server. This ranking based technique is the fundamental contrast from database query. It depends on user application the required object can be an image, audio or video. Although these objects are not saved in the IR system, but they can be in the form of metadata. An IR system computes a numeric value of query and then matches it with the ranking of similar objects.

A Study on Models and Methods of Information Retrieval System

2017 ◽  
pp. 43-68
Author(s):  
Manisha Malhotra ◽  
Aarti Singh
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Information Resources ◽  
Retrieval Process ◽  
Database Query ◽  
Text Indexing ◽  
Unique Result ◽  
The Given

Information Retrieval (IR) is the action of getting the information applicable to a data need from a pool of information resources. Searching can be depends on text indexing. Whenever a client enters an inquiry into the system, an automated information retrieval process becomes starts. Inquiries are formal statements which is required for getting an input (Rijsbergen, 1997). It is not necessary that the given query provides the relevance information. That query matches the result of required information from the database. It doesn't mean it gives the precise and unique result likewise in SQL queries (Rocchio, 2010). Its results are based on the ranking of information retrieved from server. This ranking based technique is the fundamental contrast from database query. It depends on user application the required object can be an image, audio or video. Although these objects are not saved in the IR system, but they can be in the form of metadata. An IR system computes a numeric value of query and then matches it with the ranking of similar objects.

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.

An Information Retrieval System Based on Portable Device

2013 ◽  
Vol 712-715 ◽  
pp. 2706-2711
Author(s):  
Xiao Qing Yu ◽  
Wen Gen Wang ◽  
Jian Hua Shi ◽  
Yun Hui Wang
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Relevant Information ◽  
Information Retrieval System ◽  
Text Indexing ◽  
Traditional System ◽  
Related Information ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Audio Information

Information retrieval is the activity to organize information in a certain way, and according to the users demand to find out the related information from a collection of resources. Retrieval process and technology can be based on metadata or full-text indexing. Most of the relevant information retrieval systems are devised on the computer. However, with the highly development of the embedded technology, some popular application have been developed on the platform. In this paper, we will introduce an information retrieval system on the iOS platform which is more convenient, practical, and effective compared with the traditional system. And we will introduce an application based on this system design. The experiments shown that this system was exactly effective utilized to retrieval audio information.

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.

scholarly journals Design and implementation of an effective web-based hybrid stemmer for Odia language

2020 ◽  
Vol 9 (1) ◽  
pp. 12
Author(s):  
Gouranga Charan Jena ◽  
Siddharth Swarup Rautaray
Keyword(s):  
Information Retrieval ◽  
Morphological Analysis ◽  
Retrieval System ◽  
Hybrid Approach ◽  
Information Retrieval System ◽  
Retrieval Process ◽  
Web Based ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Domain Independent

<p><span>Stemmer is used for reducing inflectional or derived word to its stem. This technique involves removing the suffix or prefix affixed in a word. It can be used for information retrieval system to refine the overall execution of the retrieval process. This process is not equivalent to morphological analysis. This process only finds the stem of a word. This technique decreases the number of terms in information retrieval system. There are various techniques exists for stemming. In this paper, a new web-based stemmer has been proposed named as “Mula” for Odia Language. It uses the Hybrid approach (i.e. combination of brute force and suffix removal approach) for Odia language. The new born stemmer is both computationally faster and domain independent. The results are favourable and indicate that the proposed stemmer can be used effectively in Odia Information Retrieval systems. This stemmer also handles the problem of over-stemming and under-stemming in some extend.</span></p>

scholarly journals Development and Integration of an Odia Stemmer in Dspace for Odia Search Engine

2020 ◽  
Vol 9 (4) ◽  
pp. 836-840
Keyword(s):  
Information Retrieval ◽  
Search Engine ◽  
Morphological Analysis ◽  
Retrieval System ◽  
Text Retrieval ◽  
Information Retrieval System ◽  
Brute Force ◽  
Retrieval Process ◽  
New Born ◽  
Domain Independent

Stemmer is used for reducing inflectional or derived word to its stem. This technique involves removing the suffix or prefix affixed in a word. It can be used for information retrieval system to refine the overall execution of the retrieval process. This process is not equivalent to morphological analysis. This process only finds the stem of a word. This technique decreases the number of terms in information retrieval system. There are various techniques exists for stemming. Here a new hybrid stemmer has developed named as “Mula” for Odia Language. It is a combination of brute force and enhanced suffix strippingapproach for Odia language. The new born stemmer is both computationally inexpensive and domain independent. We have integrated this stemmer in existing Dspace for Odia text retrieval System. The results are commendable and suggest that the new stemmer can be used effectively in Odia Search Engine. The proposed stemmer also handles over-stemming and understemming effectively

Social Networks Discovery Based on Information Retrieval Technologies and Bees Swarm Optimization

2016 ◽  
pp. 821-840
Author(s):  
Yassine Drias ◽  
Habiba Drias
Keyword(s):  
Social Networks ◽  
Information Retrieval ◽  
Retrieval System ◽  
Optimization Method ◽  
Information Retrieval System ◽  
Swarm Optimization ◽  
Large Graphs ◽  
Social Community ◽  
The Social ◽  
The Given

Unlike the previous works where detecting communities is performed on large graphs, our approach considers textual documents for discovering potential social networks. More precisely, the aim of this paper is to extract social communities from a collection of documents and a query specifying the domain of interest that may link the group. We propose a methodology that develops an information retrieval system capable to generate the documents that are in relationship with any topic. The authors of these documents are linked together to constitute the social community around the given thematic. The search process in the information retrieval system is designed using BSO, the bee swarm optimization method in order to optimize the retrieval time for large amount of documents. Our approach was implemented and tested on CACM and DBLP and the time of building a social network is quasi instant.

Information Retrieval System

2018 ◽  
Vol 9 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Ram Kumar ◽  
S. C. Sharma
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Process Performance ◽  
Retrieval Process ◽  
Complete Understanding ◽  
Relevant Document ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Performance Issues

Information Retrieval Systems (IRS) have dramatically changed the ways how people acquire information for their need. Information Retrieval (IR) enables user to find relevant document from collection of countless resources. This article presents an overview of IRS. Objectives of this article is to answer all the basic and specific questions related to IRS. In contrast to other review papers, the authors provide a complete understanding of IR in single paper. Starting from definition and importance it covers retrieval process, performance issues, and comparison among various approaches. This article also includes description of different models along with analysis of their merits and demerits. This article proposes a list of challenges, still unanswered by existing systems. Before offering a conclusion, the major applications of IR are also listed.

Research on Domain Ontology-Based Intelligent Information Retrieval System

2011 ◽  
Vol 460-461 ◽  
pp. 300-304
Author(s):  
Shu Dong Zhang ◽  
Yan Chen
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Rapid Development ◽  
Relevant Information ◽  
Domain Ontology ◽  
Information Retrieval System ◽  
Information Resources ◽  
Semantic Level ◽  
Intelligent Information Retrieval ◽  
Intelligent Information

Domain ontology introduces a new theory and method for information retrieval. In this paper, we analyze the deficiencies of traditional information retrieval and explore the relationship between domain ontology and information retrieval, as well as the basic design ideas of information retrieval based on domain ontology. Finally we present a domain ontology-based intelligent information retrieval system, so that the information retrieval can be promoted from the keyword level to the semantic level. With the rapid development of the national economy and the growth of information resources, traditional methods relying on the browser, database fields, keyword matching, or even manual retrieval query has become increasingly difficult to meet people's information retrieval needs. How to quickly and accurately identify the needed information resources has become a urgent question in front of us. Information retrieval is a technology which can find out the relevant information the user needs from a collection of large amounts of information. It has experienced manual retrieval, computer retrieval stage, now it has developed to the network and intelligent stage. The objects of information retrieval extend from a relative closed, stable and consistent, centrally managed information content by an independent database to an open, dynamic, quickly update, widely distributed, and loosely managed web content; the users of information retrieval also spread from professional intelligence agent to the common including government officials, businessmen, managers, teachers, students, professionals, etc. They ask for the higher and more diverse requirements from the results to the manner of information retrieval. Adapting to the need for network, intelligence and personalization is a new trend of information retrieval technology.

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