Enhancing Information Retrieval System Using Change-Prone Classes

2021 ◽  
pp. 566-595
Author(s):  
Deepa Bura ◽  
Amit Choudhary
Keyword(s):  
Information Retrieval ◽  
Prediction Model ◽  
Experimental Analysis ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Time Frequency ◽  
Retrieval Systems ◽  
Efficient Information ◽  
Two Phases ◽  
Sensitivity Specificity

In today's competitive world, each company is required to change software to meet changing customer requirements. At the same time, an efficient information retrieval system is required as changes made to software in different versions can lead to complicated retrieval systems. This research aims to find the association between changes and object-oriented metrics using different versions of open source software. Earlier researchers have used various techniques such as statistical methods for the prediction of change-prone classes. This research uses execution time, frequency, run time information, popularity, and class dependency in prediction of change-prone classes. For evaluating the performance of the prediction model, sensitivity, specificity, and ROC curve are used. Higher values of AUC indicate the prediction model gives accurate results. Results are validated in two phases: Experimental Analysis I validates results using OpenClinic software and OpenHospital software and Experimental Analysis II validates result using Neuroph 2.9.2 and Neuroph 2.6.

Enhancing Information Retrieval System Using Change-Prone Classes

2020 ◽  
pp. 40-68 ◽  
Author(s):  
Deepa Bura ◽  
Amit Choudhary
Keyword(s):  
Information Retrieval ◽  
Prediction Model ◽  
Experimental Analysis ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Time Frequency ◽  
Retrieval Systems ◽  
Efficient Information ◽  
Two Phases ◽  
Sensitivity Specificity

In today's competitive world, each company is required to change software to meet changing customer requirements. At the same time, an efficient information retrieval system is required as changes made to software in different versions can lead to complicated retrieval systems. This research aims to find the association between changes and object-oriented metrics using different versions of open source software. Earlier researchers have used various techniques such as statistical methods for the prediction of change-prone classes. This research uses execution time, frequency, run time information, popularity, and class dependency in prediction of change-prone classes. For evaluating the performance of the prediction model, sensitivity, specificity, and ROC curve are used. Higher values of AUC indicate the prediction model gives accurate results. Results are validated in two phases: Experimental Analysis I validates results using OpenClinic software and OpenHospital software and Experimental Analysis II validates result using Neuroph 2.9.2 and Neuroph 2.6.

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.

An Information Retrieval System Based on Multiple Portlets

2021 ◽  
Vol 13 (1) ◽  
pp. 74-86
Author(s):  
Glauber José Vaz ◽  
Jayme Garcia Arnal Barbedo
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Service Oriented Architecture ◽  
Information Retrieval System ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Single User Interface ◽  
Service Oriented ◽  
Single User ◽  
Aggregated Search

Information retrieval systems built with a service-oriented architecture have numerous advantages, and portlets are a key technology to implement services which interact with each other in the presentation layer. This work presents an efficient approach for the communication between the components of an information retrieval system based on multiple portlets in a single user interface. It also presents the architecture and the main methods of the system implemented as a case of use for this approach. It is shown that the proposed solution yields the best inter-portlet communication mechanism in each situation, while possessing the ability to deliver aggregated search and superior user experience.

Method of Lexical Enrichment in Information Retrieval System in Arabic

2013 ◽  
Vol 3 (4) ◽  
pp. 35-51 ◽  
Author(s):  
Souheyl Mallat ◽  
Anis Zouaghi ◽  
Emna Hkiri ◽  
Mounir Zrigui
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Semantic Analysis ◽  
Contextual Information ◽  
Information Retrieval System ◽  
Enrichment Method ◽  
Weighting Functions ◽  
Retrieval Systems ◽  
Significant Term ◽  
Information Retrieval Systems

In this paper, the authors propose a method for lexical enrichment of Arabic queries in order to improve the performance of the information retrieval systems SRI. This method has two types of enrichment: linguistic and contextual. The first one is based on the linguistic analysis (lemmatization, morphological, syntactic and semantic analysis), whose goal is to generate a descriptive list (list-desc). This list contains a set of linguistic lexicon assigned to each significant term in the query. The second enrichment consists in integrating contextual information derived from the corpus documents. It is based on statistical analysis using Salton weighting functions: TF-IDF and TF-IEF. The TF-IDF function is applied on the list-desc and documents in the corpus in order to identify relevant documents. TF-IEF function is made between the list-desc and sentences belonging to the relevant documents to identify relevant sentences. Then, terms in these sentences are weighted, and those with highest weights are considered rich in terms of informative and contextual importance are added to the original query. The authors' lexical enrichment method was evaluated on a corpus of documents belonging to a specialized domain and results show its interest in terms of precision and recall.

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>

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.

What does good look like?

2019 ◽  
Vol 53 (2) ◽  
pp. 76-81
Author(s):  
Theo Huibers ◽  
Monica Landoni ◽  
Maria Soledad Pera ◽  
Jerry Alan Fails ◽  
Emiliana Murgia ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Graduate Students ◽  
Computer Science ◽  
Interaction Design ◽  
Retrieval System ◽  
Short Review ◽  
Information Retrieval System ◽  
Good Information ◽  
Retrieval Systems ◽  
Information Retrieval Systems

This short review discusses the outcomes of the 3 rd Workshop of the International and Interdisciplinary Perspectives on Children & Recommender and Information Retrieval Systems (KidRec 2019) , co-located with the 2019 ACM Interaction Design and Children (IDC) Conference, which took place June 12-15 in Boise, Idaho, USA. The goal for the workshop was to explore the characteristics of a "good" information retrieval system for children. The diversity of attendees - including industry representatives, undergraduate and graduate students, and senior scholars in various areas of computer science - made it possible to continue to build community around this important topic and further discuss and outline the salient concerns and the next steps to promote further exploration in this area.

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