On the role of subjectivity in establishing, using, operating and evaluating information retrieval systems. Treatise II on retrieval system theory

1973 ◽  
Vol 9 (7) ◽  
pp. 353-372 ◽  
Author(s):  
Robert Fugmann
Keyword(s):  
System Theory ◽  
Information Retrieval ◽  
Retrieval System ◽  
Retrieval Systems ◽  
Information Retrieval Systems

scholarly journals Роль термінів-непрямих номінацій у тезаурусі інформаційно-пошукової системи славістичного мовознавства

2014 ◽  
Vol 49 ◽  
pp. 150-163
Author(s):  
Євгенія A. [IEvheniia A.] Карпіловська [Karpilovs’ka]
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Scientific Publications ◽  
Linguistic Support ◽  
Slavic Linguistics ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Terminology System ◽  
Slavic Studies

The role of terms-indirect nominations in the thesaurus of information retrieval system of the Slavic linguisticsThe article examines some of the problems of modern information retrieval systems in the Slavic studies, in particular, one of the most representative – Bibliographic Database World Slavonic Linguistics, created in the Institute of Slavic Studies of PAS under the leadership of Dr. Z. E. Rudnik-Karwatova. The author focuses on the ways to improve the linguistic support of such systems and increase the efficiency of image for information searching. They are connected with the study of the keywords in the annotations of scientific publications within database, as well as in the whole of modern Slavic linguistic terminology. This study enables us not only to select a comprehensive number of terms for each linguistic discipline, school, or problem, but also to determine their variability as well as their relationship with other terms of modern-­day Slavic linguistics. The result of such study should be information retrieval thesaurus of modern Slavic linguistic terminology.Special attention in the article is paid to the role of indirect nomination in modern Slavic linguistic terminology, system-organizing function of the terms with indirect semantics, resources and modes of their creating in different Slavonic languages, the correlation between indirect nomination and figurative one as well as the terms which indicate the place of object in some classifications (see Ukrainian середній рід) or gradual opposition (see Polish semileksem).

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.

Enhanced Spoken Sentence Retrieval Using a Conventional Automatic Speech Recognizer in Smart Home

2016 ◽  
Vol 25 (03) ◽  
pp. 1650017 ◽  
Author(s):  
Hyeokju Ahn ◽  
Harksoo Kim
Keyword(s):  
Information Retrieval ◽  
Smart Home ◽  
Retrieval System ◽  
Generation Model ◽  
Query Term ◽  
Post Processing ◽  
Retrieval Systems ◽  
Sentence Retrieval ◽  
Information Retrieval Systems ◽  
Performance Results

With the rapid evolution of smart home environment, the demand for spoken information retrieval (e.g., voice-activated FAQ retrieval) on information appliances is increasing. In spoken information retrieval, users’ spoken queries are converted into text queries using automatic speech recognition (ASR) engines. If top-1 results of the ASR engines are incorrect, the errors are propagated to information retrieval systems. If a document collection is a small set of sentences such as frequently asked questions (FAQs), the errors have additional effect on the performance of information retrieval systems. To improve the performance of such a sentence retrieval system, we propose a post-processing model of an ASR engine. The post-processing model consists of a re-ranking and a query term generation model. The re-ranking model rearranges top-n outputs of the ASR engines using the ranking support vector machine (Ranking SVM). The query term generation model extracts meaningful content words from the re-ranked queries based on term frequencies and query rankings. In the experiments, the re-ranking model improved the top-1 performance results of an underlying ASR engine with 4.4% higher precision and 6.4% higher recall rate. The query term generation model improved the performance results of an underlying information retrieval system with an accuracy 2.4% to 2.6% higher. Based on the experimental result, the proposed model revealed that it could improve the performance of a spoken sentence retrieval system in a restricted domain.

Information Retrieval Models

2017 ◽  
pp. 17-42 ◽  
Author(s):  
Saruladha Krishnamurthy ◽  
Akila V
Keyword(s):  
Information Retrieval ◽  
Research Field ◽  
Process Models ◽  
Retrieval Models ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
External Sources ◽  
Active Research ◽  
Cross Lingual

Information retrieval is currently an active research field with the evolution of World wide web. The objective of this chapter is to provide an insight into the information retrieval definitions, process, models. Further how traditional information retrieval has evolved and adapted for search engines is also discussed. The information retrieval models have not only been used for search purpose it also supports cross lingual translation and retrieval tasks. This chapter also outlines the CLIR process in a brief manner. The tools which are usually used for experimental and research purpose is also discussed. This chapter is organized as Introduction to the concepts of information retrieval. Description of the information retrieval process, the information retrieval models, the role of external sources like ontologies in information retrieval systems. Finally the chapter provides an overview of CLIR and the tools used in developing IR systems is mentioned. Further the latest research directions in IR is explained.

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 Information Retrieval Models

2018 ◽  
pp. 995-1015
Author(s):  
Saruladha Krishnamurthy ◽  
Akila V
Keyword(s):  
Information Retrieval ◽  
Research Field ◽  
Process Models ◽  
Retrieval Models ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
External Sources ◽  
Active Research ◽  
Cross Lingual

Information retrieval is currently an active research field with the evolution of World wide web. The objective of this chapter is to provide an insight into the information retrieval definitions, process, models. Further how traditional information retrieval has evolved and adapted for search engines is also discussed. The information retrieval models have not only been used for search purpose it also supports cross lingual translation and retrieval tasks. This chapter also outlines the CLIR process in a brief manner. The tools which are usually used for experimental and research purpose is also discussed. This chapter is organized as Introduction to the concepts of information retrieval. Description of the information retrieval process, the information retrieval models, the role of external sources like ontologies in information retrieval systems. Finally the chapter provides an overview of CLIR and the tools used in developing IR systems is mentioned. Further the latest research directions in IR is explained.

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.

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