Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 27

Information Retrieval Related Publications

27 AINA: Disney Animation Information as Educational Resources

Authors: Piedad Garrido, Julio A. Sanguesa, Fernando Repulles, Andy Bloor, Jesus Gallardo, Vicente Torres, Jesus Tramullas

Abstract:

With the emergence and development of Information and Communications Technologies (ICTs), Higher Education is experiencing rapid changes, not only in its teaching strategies but also in student’s learning skills. However, we have noticed that students often have difficulty when seeking innovative, useful, and interesting learning resources for their work. This is due to the lack of supervision in the selection of good query tools. This paper presents AINA, an Information Retrieval (IR) computer system aimed at providing motivating and stimulating content to both students and teachers working on different areas and at different educational levels. In particular, our proposal consists of an open virtual resource environment oriented to the vast universe of Disney comics and cartoons. Our test suite includes Disney’s long and shorts films, and we have performed some activities based on the Just In Time Teaching (JiTT) methodology. More specifically, it has been tested by groups of university and secondary school students.

Keywords: Animation, Information Retrieval, Educational Resources, JiTT

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26 Domain Driven Design vs Soft Domain Driven Design Frameworks

Authors: Mohammed Salahat, Steve Wade

Abstract:

This paper presents and compares the SSDDD “Systematic Soft Domain Driven Design Framework” to DDD “Domain Driven Design Framework” as a soft system approach of information systems development. The framework use SSM as a guiding methodology within which we have embedded a sequence of design tasks based on the UML leading to the implementation of a software system using the Naked Objects framework. This framework has been used in action research projects that have involved the investigation and modelling of business processes using object-oriented domain models and the implementation of software systems based on those domain models. Within this framework, Soft Systems Methodology (SSM) is used as a guiding methodology to explore the problem situation and to develop the domain model using UML for the given business domain. The framework is proposed and evaluated in our previous works, a comparison between SSDDD and DDD is presented in this paper, to show how SSDDD improved DDD as an approach to modelling and implementing business domain perspectives for Information Systems Development. The comparison process, the results, and the improvements are presented in the following sections of this paper.

Keywords: Information Retrieval, UML, SSM, domain-driven design, soft domain-driven design, naked objects, soft language, multimethodology

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25 Personalization of Web Search Using Web Page Clustering Technique

Authors: Pradeep M. Patil, Amol Bapuso Rajmane, Prakash J. Kulkarni

Abstract:

The Information Retrieval community is facing the problem of effective representation of Web search results. When we organize web search results into clusters it becomes easy to the users to quickly browse through search results. The traditional search engines organize search results into clusters for ambiguous queries, representing each cluster for each meaning of the query. The clusters are obtained according to the topical similarity of the retrieved search results, but it is possible for results to be totally dissimilar and still correspond to the same meaning of the query. People search is also one of the most common tasks on the Web nowadays, but when a particular person’s name is queried the search engines return web pages which are related to different persons who have the same queried name. By placing the burden on the user of disambiguating and collecting pages relevant to a particular person, in this paper, we have developed an approach that clusters web pages based on the association of the web pages to the different people and clusters that are based on generic entity search.

Keywords: Information Retrieval, Clustering, Entity resolution, graph based disambiguation, web people search

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24 Business Domain Modelling Using an Integrated Framework

Authors: Mohammed Salahat, Steve Wade

Abstract:

This paper presents an application of a “Systematic Soft Domain Driven Design Framework” as a soft systems approach to domain-driven design of information systems development. The framework use SSM as a guiding methodology within which we have embedded a sequence of design tasks based on the UML leading to the implementation of a software system using the Naked Objects framework. This framework have been used in action research projects that have involved the investigation and modelling of business processes using object-oriented domain models and the implementation of software systems based on those domain models. Within this framework, Soft Systems Methodology (SSM) is used as a guiding methodology to explore the problem situation and to develop the domain model using UML for the given business domain. The framework is proposed and evaluated in our previous works, and a real case study “Information Retrieval System for academic research” is used, in this paper, to show further practice and evaluation of the framework in different business domain. We argue that there are advantages from combining and using techniques from different methodologies in this way for business domain modelling. The framework is overviewed and justified as multimethodology using Mingers multimethodology ideas.

Keywords: Information Retrieval, UML, SSM, domain-driven design, naked objects, soft language, multimethodology, soft domaindriven design

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23 Information Retrieval: A Comparative Study of Textual Indexing Using an Oriented Object Database (db4o) and the Inverted File

Authors: Mohammed Erritali

Abstract:

The growth in the volume of text data such as books and articles in libraries for centuries has imposed to establish effective mechanisms to locate them. Early techniques such as abstraction, indexing and the use of classification categories have marked the birth of a new field of research called "Information Retrieval". Information Retrieval (IR) can be defined as the task of defining models and systems whose purpose is to facilitate access to a set of documents in electronic form (corpus) to allow a user to find the relevant ones for him, that is to say, the contents which matches with the information needs of the user. Most of the models of information retrieval use a specific data structure to index a corpus which is called "inverted file" or "reverse index". This inverted file collects information on all terms over the corpus documents specifying the identifiers of documents that contain the term in question, the frequency of each term in the documents of the corpus, the positions of the occurrences of the word... In this paper we use an oriented object database (db4o) instead of the inverted file, that is to say, instead to search a term in the inverted file, we will search it in the db4o database. The purpose of this work is to make a comparative study to see if the oriented object databases may be competing for the inverse index in terms of access speed and resource consumption using a large volume of data.

Keywords: Information Retrieval, indexation, inverted file, oriented object database (db4o)

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22 Role of Natural Language Processing in Information Retrieval; Challenges and Opportunities

Authors: Khaled M. Alhawiti

Abstract:

This paper aims to analyze the role of natural language processing (NLP). The paper will discuss the role in the context of automated data retrieval, automated question answer, and text structuring. NLP techniques are gaining wider acceptance in real life applications and industrial concerns. There are various complexities involved in processing the text of natural language that could satisfy the need of decision makers. This paper begins with the description of the qualities of NLP practices. The paper then focuses on the challenges in natural language processing. The paper also discusses major techniques of NLP. The last section describes opportunities and challenges for future research.

Keywords: Information Retrieval, data retrieval, text structuring, Natural Language Processing

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21 Comparative Analysis of Different Page Ranking Algorithms

Authors: K. Duraiswamy, S. Prabha, J. Indhumathi

Abstract:

Search engine plays an important role in internet, to retrieve the relevant documents among the huge number of web pages. However, it retrieves more number of documents, which are all relevant to your search topics. To retrieve the most meaningful documents related to search topics, ranking algorithm is used in information retrieval technique. One of the issues in data miming is ranking the retrieved document. In information retrieval the ranking is one of the practical problems. This paper includes various Page Ranking algorithms, page segmentation algorithms and compares those algorithms used for Information Retrieval. Diverse Page Rank based algorithms like Page Rank (PR), Weighted Page Rank (WPR), Weight Page Content Rank (WPCR), Hyperlink Induced Topic Selection (HITS), Distance Rank, Eigen Rumor, Distance Rank Time Rank, Tag Rank, Relational Based Page Rank and Query Dependent Ranking algorithms are discussed and compared.

Keywords: Information Retrieval, Web mining, Web Page Ranking, search engine, page segmentations

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20 A Comparative Analysis of Different Web Content Mining Tools

Authors: N. Shanthi, T. Suresh Kumar, M. Arthanari

Abstract:

Nowadays, the Web has become one of the most pervasive platforms for information change and retrieval. It collects the suitable and perfectly fitting information from websites that one requires. Data mining is the form of extracting data’s available in the internet. Web mining is one of the elements of data mining Technique, which relates to various research communities such as information recovery, folder managing system and simulated intellects. In this Paper we have discussed the concepts of Web mining. We contain generally focused on one of the categories of Web mining, specifically the Web Content Mining and its various farm duties. The mining tools are imperative to scanning the many images, text, and HTML documents and then, the result is used by the various search engines. We conclude by presenting a comparative table of these tools based on some pertinent criteria.

Keywords: Data Mining, Information Retrieval, Web mining, web content mining, Mining Tools

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19 Identification of Coauthors in Scientific Database

Authors: Gray F. Moita, Thiago M. R Dias

Abstract:

The analysis of scientific collaboration networks has contributed significantly to improving the understanding of how does the process of collaboration between researchers and also to understand how the evolution of scientific production of researchers or research groups occurs. However, the identification of collaborations in large scientific databases is not a trivial task given the high computational cost of the methods commonly used. This paper proposes a method for identifying collaboration in large data base of curriculum researchers. The proposed method has low computational cost with satisfactory results, proving to be an interesting alternative for the modeling and characterization of large scientific collaboration networks.

Keywords: Information Retrieval, scientific collaboration, extraction and data integration

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18 A Review on Important Aspects of Information Retrieval

Authors: ASHISH SAINI, YOGESH GUPTA, A.K. Saxena

Abstract:

Information retrieval has become an important field of study and research under computer science due to explosive growth of information available in the form of full text, hypertext, administrative text, directory, numeric or bibliographic text. The research work is going on various aspects of information retrieval systems so as to improve its efficiency and reliability. This paper presents a comprehensive study, which discusses not only emergence and evolution of information retrieval but also includes different information retrieval models and some important aspects such as document representation, similarity measure and query expansion.

Keywords: Information Retrieval, query expansion, similarity measure, vector space model

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17 Analyzing the Relation of Community Group for Research Paper Bookmarking by Using Association Rule

Authors: P. Jomsri

Abstract:

Currently searching through internet is very popular especially in a field of academic. A huge of educational information such as research papers are overload for user. So community-base web sites have been developed to help user search information more easily from process of customizing a web site to need each specifies user or set of user. In this paper propose to use association rule analyze the community group on research paper bookmarking. A set of design goals for community group frameworks is developed and discussed. Additionally Researcher analyzes the initial relation by using association rule discovery between the antecedent and the consequent of a rule in the groups of user for generate the idea to improve ranking search result and development recommender system.

Keywords: Information Retrieval, association rule, research paper bookmarking

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16 Mining and Visual Management of XML-Based Image Collections

Authors: Khalil Shihab, Nida Al-Chalabi

Abstract:

This article describes Uruk, the virtual museum of Iraq that we developed for visual exploration and retrieval of image collections. The system largely exploits the loosely-structured hierarchy of XML documents that provides a useful representation method to store semi-structured or unstructured data, which does not easily fit into existing database. The system offers users the capability to mine and manage the XML-based image collections through a web-based Graphical User Interface (GUI). Typically, at an interactive session with the system, the user can browse a visual structural summary of the XML database in order to select interesting elements. Using this intermediate result, queries combining structure and textual references can be composed and presented to the system. After query evaluation, the full set of answers is presented in a visual and structured way.

Keywords: Information Retrieval, Case-based Reasoning, Fuzzy Sets, Graphical User Interfaces, Data-centric XML

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15 A Combination of Similarity Ranking and Time for Social Research Paper Searching

Authors: P. Jomsri

Abstract:

Nowadays social media are important tools for web resource discovery. The performance and capabilities of web searches are vital, especially search results from social research paper bookmarking. This paper proposes a new algorithm for ranking method that is a combination of similarity ranking with paper posted time or CSTRank. The paper posted time is static ranking for improving search results. For this particular study, the paper posted time is combined with similarity ranking to produce a better ranking than other methods such as similarity ranking or SimRank. The retrieval performance of combination rankings is evaluated using mean values of NDCG. The evaluation in the experiments implies that the chosen CSTRank ranking by using weight score at ratio 90:10 can improve the efficiency of research paper searching on social bookmarking websites.

Keywords: Information Retrieval, Time, similarity ranking, combination ranking, static ranking, weight score

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14 Automatic Building an Extensive Arabic FA Terms Dictionary

Authors: El-Sayed Atlam, Masao Fuketa, Kazuhiro Morita, Jun-ichi Aoe

Abstract:

Field Association (FA) terms are a limited set of discriminating terms that give us the knowledge to identify document fields which are effective in document classification, similar file retrieval and passage retrieval. But the problem lies in the lack of an effective method to extract automatically relevant Arabic FA Terms to build a comprehensive dictionary. Moreover, all previous studies are based on FA terms in English and Japanese, and the extension of FA terms to other language such Arabic could be definitely strengthen further researches. This paper presents a new method to extract, Arabic FA Terms from domain-specific corpora using part-of-speech (POS) pattern rules and corpora comparison. Experimental evaluation is carried out for 14 different fields using 251 MB of domain-specific corpora obtained from Arabic Wikipedia dumps and Alhyah news selected average of 2,825 FA Terms (single and compound) per field. From the experimental results, recall and precision are 84% and 79% respectively. Therefore, this method selects higher number of relevant Arabic FA Terms at high precision and recall.

Keywords: Information Retrieval, information extraction, Document Classification, Arabic Field Association Terms

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13 Text Summarization for Oil and Gas News Article

Authors: L. H. Chong, Y. Y. Chen

Abstract:

Information is increasing in volumes; companies are overloaded with information that they may lose track in getting the intended information. It is a time consuming task to scan through each of the lengthy document. A shorter version of the document which contains only the gist information is more favourable for most information seekers. Therefore, in this paper, we implement a text summarization system to produce a summary that contains gist information of oil and gas news articles. The summarization is intended to provide important information for oil and gas companies to monitor their competitor-s behaviour in enhancing them in formulating business strategies. The system integrated statistical approach with three underlying concepts: keyword occurrences, title of the news article and location of the sentence. The generated summaries were compared with human generated summaries from an oil and gas company. Precision and recall ratio are used to evaluate the accuracy of the generated summary. Based on the experimental results, the system is able to produce an effective summary with the average recall value of 83% at the compression rate of 25%.

Keywords: Information Retrieval, Text Summarization, statistical approach

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12 A Weighted-Profiling Using an Ontology Basefor Semantic-Based Search

Authors: Hikmat A. M. Abd-El-Jaber, Tengku M. T. Sembok

Abstract:

The information on the Web increases tremendously. A number of search engines have been developed for searching Web information and retrieving relevant documents that satisfy the inquirers needs. Search engines provide inquirers irrelevant documents among search results, since the search is text-based rather than semantic-based. Information retrieval research area has presented a number of approaches and methodologies such as profiling, feedback, query modification, human-computer interaction, etc for improving search results. Moreover, information retrieval has employed artificial intelligence techniques and strategies such as machine learning heuristics, tuning mechanisms, user and system vocabularies, logical theory, etc for capturing user's preferences and using them for guiding the search based on the semantic analysis rather than syntactic analysis. Although a valuable improvement has been recorded on search results, the survey has shown that still search engines users are not really satisfied with their search results. Using ontologies for semantic-based searching is likely the key solution. Adopting profiling approach and using ontology base characteristics, this work proposes a strategy for finding the exact meaning of the query terms in order to retrieve relevant information according to user needs. The evaluation of conducted experiments has shown the effectiveness of the suggested methodology and conclusion is presented.

Keywords: Semantic Web, Information Retrieval, Ontology, search engine, user profiles

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11 Mining Association Rules from Unstructured Documents

Authors: Hany Mahgoub

Abstract:

This paper presents a system for discovering association rules from collections of unstructured documents called EART (Extract Association Rules from Text). The EART system treats texts only not images or figures. EART discovers association rules amongst keywords labeling the collection of textual documents. The main characteristic of EART is that the system integrates XML technology (to transform unstructured documents into structured documents) with Information Retrieval scheme (TF-IDF) and Data Mining technique for association rules extraction. EART depends on word feature to extract association rules. It consists of four phases: structure phase, index phase, text mining phase and visualization phase. Our work depends on the analysis of the keywords in the extracted association rules through the co-occurrence of the keywords in one sentence in the original text and the existing of the keywords in one sentence without co-occurrence. Experiments applied on a collection of scientific documents selected from MEDLINE that are related to the outbreak of H5N1 avian influenza virus.

Keywords: Information Retrieval, Text Mining, Association Rules, knowledgediscovery in text

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10 Mining News Sites to Create Special Domain News Collections

Authors: David B. Bracewell, Fuji Ren, Shingo Kuroiwa

Abstract:

We present a method to create special domain collections from news sites. The method only requires a single sample article as a seed. No prior corpus statistics are needed and the method is applicable to multiple languages. We examine various similarity measures and the creation of document collections for English and Japanese. The main contributions are as follows. First, the algorithm can build special domain collections from as little as one sample document. Second, unlike other algorithms it does not require a second “general" corpus to compute statistics. Third, in our testing the algorithm outperformed others in creating collections made up of highly relevant articles.

Keywords: Information Retrieval, news, Special DomainCollections

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9 Advanced Information Extraction with n-gram based LSI

Authors: Oya Kalıpsız, Ahmet Güven, Ö. Özgür Bozkurt

Abstract:

Number of documents being created increases at an increasing pace while most of them being in already known topics and little of them introducing new concepts. This fact has started a new era in information retrieval discipline where the requirements have their own specialties. That is digging into topics and concepts and finding out subtopics or relations between topics. Up to now IR researches were interested in retrieving documents about a general topic or clustering documents under generic subjects. However these conventional approaches can-t go deep into content of documents which makes it difficult for people to reach to right documents they were searching. So we need new ways of mining document sets where the critic point is to know much about the contents of the documents. As a solution we are proposing to enhance LSI, one of the proven IR techniques by supporting its vector space with n-gram forms of words. Positive results we have obtained are shown in two different application area of IR domain; querying a document database, clustering documents in the document database.

Keywords: Information Retrieval, information extraction, Document Clustering, LSI, n-gram

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8 Using Genetic Algorithm to Improve Information Retrieval Systems

Authors: Ahmed A. A. Radwan, Bahgat A. Abdel Latef, Abdel Mgeid A. Ali, Osman A. Sadek

Abstract:

This study investigates the use of genetic algorithms in information retrieval. The method is shown to be applicable to three well-known documents collections, where more relevant documents are presented to users in the genetic modification. In this paper we present a new fitness function for approximate information retrieval which is very fast and very flexible, than cosine similarity fitness function.

Keywords: Information Retrieval, cosine similarity, fitness function, Genetic Algorithm, Query learning

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7 A Frame Work for Query Results Refinement in Multimedia Databases

Authors: Humaira Liaquat, Nadeem Iftikhar, Shaukat Ali, Zohaib Zafar Iqbal

Abstract:

In the current age, retrieval of relevant information from massive amount of data is a challenging job. Over the years, precise and relevant retrieval of information has attained high significance. There is a growing need in the market to build systems, which can retrieve multimedia information that precisely meets the user's current needs. In this paper, we have introduced a framework for refining query results before showing it to the user, using ambient intelligence, user profile, group profile, user location, time, day, user device type and extracted features. A prototypic tool was also developed to demonstrate the efficiency of the proposed approach.

Keywords: Information Retrieval, Ambient intelligence, multimedia databases, Context aware retrieval, User and group profile

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6 Enhancing Retrieval Effectiveness of Malay Documents by Exploiting Implicit Semantic Relationship between Words

Authors: Mohd Pouzi Hamzah, Tengku Mohd Tengku Sembok

Abstract:

Phrases has a long history in information retrieval, particularly in commercial systems. Implicit semantic relationship between words in a form of BaseNP have shown significant improvement in term of precision in many IR studies. Our research focuses on linguistic phrases which is language dependent. Our results show that using BaseNP can improve performance although above 62% of words formation in Malay Language based on derivational affixes and suffixes.

Keywords: Information Retrieval, Malay language, Semantic Relationship, Retrieval Effectiveness, Conceptual Indexing

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5 Word Stemming Algorithms and Retrieval Effectiveness in Malay and Arabic Documents Retrieval Systems

Authors: Tengku Mohd T. Sembok

Abstract:

Documents retrieval in Information Retrieval Systems (IRS) is generally about understanding of information in the documents concern. The more the system able to understand the contents of documents the more effective will be the retrieval outcomes. But understanding of the contents is a very complex task. Conventional IRS apply algorithms that can only approximate the meaning of document contents through keywords approach using vector space model. Keywords may be unstemmed or stemmed. When keywords are stemmed and conflated in retrieving process, we are a step forwards in applying semantic technology in IRS. Word stemming is a process in morphological analysis under natural language processing, before syntactic and semantic analysis. We have developed algorithms for Malay and Arabic and incorporated stemming in our experimental systems in order to measure retrieval effectiveness. The results have shown that the retrieval effectiveness has increased when stemming is used in the systems.

Keywords: Artificial Intelligence, Information Retrieval, natural language processing

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4 Highlighting Document's Structure

Authors: Sylvie Ratté, Wilfried Njomgue, Pierre-André Ménard

Abstract:

In this paper, we present symbolic recognition models to extract knowledge characterized by document structures. Focussing on the extraction and the meticulous exploitation of the semantic structure of documents, we obtain a meaningful contextual tagging corresponding to different unit types (title, chapter, section, enumeration, etc.).

Keywords: Information Retrieval, document structures, symbolic grammars

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3 Context-Aware Querying in Multimedia Databases – A Futuristic Approach

Authors: Nadeem Iftikhar, Shaukat Ali, Zouhaib Zafar

Abstract:

Efficient retrieval of multimedia objects has gained enormous focus in recent years. A number of techniques have been suggested for retrieval of textual information; however, relatively little has been suggested for efficient retrieval of multimedia objects. In this paper we have proposed a generic architecture for contextaware retrieval of multimedia objects. The proposed framework combines the well-known approaches of text-based retrieval and context-aware retrieval to formulate architecture for accurate retrieval of multimedia data.

Keywords: Information Retrieval, multimedia databases, Context-aware retrieval, multimedia data

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2 Cross-Search Technique and its Visualization of Peer-to-Peer Distributed Clinical Documents

Authors: Yong Jun Choi, Juman Byun, Simon Berkovich

Abstract:

One of the ubiquitous routines in medical practice is searching through voluminous piles of clinical documents. In this paper we introduce a distributed system to search and exchange clinical documents. Clinical documents are distributed peer-to-peer. Relevant information is found in multiple iterations of cross-searches between the clinical text and its domain encyclopedia.

Keywords: Information Retrieval, Peer-to-Peer, Clinical documents, cross-search, document exchange

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1 A Comparative Performance Evaluation Model of Mobile Agent Versus Remote Method Invocation for Information Retrieval

Authors: Magdy Saeb, Yousry El-Gamal, Khalid El-Gazzar

Abstract:

The development of distributed systems has been affected by the need to accommodate an increasing degree of flexibility, adaptability, and autonomy. The Mobile Agent technology is emerging as an alternative to build a smart generation of highly distributed systems. In this work, we investigate the performance aspect of agent-based technologies for information retrieval. We present a comparative performance evaluation model of Mobile Agents versus Remote Method Invocation by means of an analytical approach. We demonstrate the effectiveness of mobile agents for dynamic code deployment and remote data processing by reducing total latency and at the same time producing minimum network traffic. We argue that exploiting agent-based technologies significantly enhances the performance of distributed systems in the domain of information retrieval.

Keywords: Distributed Systems, Information Retrieval, Database, Mobile Agent, Performance Evaluation, RMI

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