Quality Of Information Retrieval Research Articles

KEGIATAN PENGATALOGAN DI PERPUSTAKAAN KELUARGA EFENDI

In the information era that is growing rapidly and increasingly advanced as it is today, the public's need for information is growing rapidly. Family libraries play an important role in meeting information needs, especially the information needs of library members. Although the scope of the family library is narrow because library members only consist of family members and/or family relatives, but with the existence of a family library, family library members can find their own information needs. Examine how to process library materials in the family library, namely the Efendi Family Library to facilitate users of the Efendi Family Library. This study uses a qualitative descriptive research method. The object of this research is the cataloging system in the Efendi Family Library. This research was conducted from November 15 to December 6, 2021 at the Efendi Family Library. Bibliography regarding the increasing number of user information needs and various user characteristics, the bibliography is used as an effort to improve the quality of information retrieval quickly and accurately. Senayan Library Management system (SLiMS) is a web-based Open Source Software (OSS) to meet the needs of library automation from small to large scale. The utilization of the Senayan Library Management system (SLiMS) application at the Efendi Family Library has not been said to be optimal because it has not utilized the features contained in the Senayan Library Management system (SLiMS) application.

Intelligent retrieval method of mobile learning resources in the intelligent higher education system

Mobile learning has become more important for the new generation. It helps students think better, pushes them to study more deeply, and leads them to significant knowledge production. Mobile learning (mobile learning) is a learning paradigm that enables students to get resources from mobile technology and the Internet everywhere and anytime. The mobile learning components should be appropriately arranged. The interactions between the different components should be combined effectively and optimally for m-learning to be successful and effective. It is important to arrange the features of mobile learning and how they are applied to mobile learning activities, the application procedures, and the duration of the application time well in advance. In this paper, Human-interaction machine-based intelligent retrieved (HIM-IR) method has been suggested to improve student performance using mobile education. In mobile learning, students would find information through the network. Thus, the retrieval of quality information in support services is quite crucial. Mobile intelligent recovery would help the intelligence engine for mobile learning. The existing web server has technology on the server that doesn't have great precision and intelligence. The input string format is necessary for the retrieval process. The proposed methods aim to define the fundamental aspects and features of mobile learning in new trends in technological development. HIM-IR can be beneficial for anyone engaged in mobile learning design, preparation, and implementation.

A Theoretical Approach For Developing A Semantic Analysis IIR Tool

An IIR (intelligent information retrieval) is a machine learning system used by users to retrieve the massive volume of information available through the internet. IIR offers personalization and efficiency in the current internet development allowing users to examine and acquire appropriate information. The paper will focus on the keyword searching issues of the current digital library system. The proposal is to choose a model that solves the issue using metadata case base and concept-based approach. The aim is to introduce a set of categories and concepts in the domain field that demonstrates some relations between them. As a result, poor quality of information retrieval in digital library system will be solved. The experiment has demonstrated that the already developed domain-specific ontology can be efficient for query advancement. Many researchers have used semantic retrieval technology using concepts to solve problems that lack semantics in traditional retrieval technology. Using concepts in ontology enhances search results.

THE RELATIONSHIP BETWEEN INFORMATION SEARCH AND PROVISION OF INTERLIBRARY SERVICES

The search for the requested document is one of the most important processes in the provision of interlibrary services. At the same time, it becomes quite difficult to conduct search procedures in a variety of information retrieval systems (IRS) that operate according to certain rules. This problem requires constant study as new technical search solutions are emerging that need to be mastered by experienced users and novices in the expanding digital workspace. The purpose of the article is to show the existing possibilities for improving the quality of information retrieval in the IRS to meet user orders. The objectives of the research are to uncover the main causes of users’ dissatisfaction with information search in interactive systems and to identify ways to improve them. A brief overview of the history of development and transformations in the use of the reference and retrieval apparatus in interlibrary services is given. Positive changes were noted in the search for documents related to the use of information and communication technologies, as well as the contribution of employees of the information and library sphere to the creation and operation of electronic catalogs. The profound interrelationship of the processes of interlibrary services, the relevance of searching and the implementation of high technology is emphasized. Special attention is paid to the analysis of foreign scientific publications 2015–2019. They covered the use of IRS, search models, the dissatisfaction with search, the improvement of efficiency and modernization of systems, the prospects for their development. The article summarizes scientific and practical results of information search in relation to interlibrary services in domestic and foreign online systems of information and library institutions. The novelty of the article is that it focuses on the study of the effectiveness of IRS, which fundamentally affects users’ satisfaction with interlibrary services.

Application of Quicksort Algorithm in Information Retrieval

With the development and progress of today’s network information technology, a variety of large-scale network databases have emerged with the situation, such as Baidu Library and Weipu Database, the number of documents in the inventory has reached nearly one million. So how do you quickly and effectively retrieve the information you want in such a huge database? This requires finding efficient algorithms to reduce the computational complexity of the computer during Information Retrieval, improve retrieval efficiency, and adapt to the rapid expansion of document data. The Quicksort Algorithm gives different weights to each position of the document, and multiplies the weight of each position with the number of matches of that position, and then adds all the multiplied sums to set a feature value for Quicksort, which can achieve the full accuracy of Information Retrieval. Therefore, the purpose of this paper is to use the quick sort algorithm to increase the speed of Information Retrieval, and to use the position weighting algorithm to improve the matching quality of Information Retrieval, so as to achieve the overall effect of improving the efficiency of Information Retrieval.

A Question-Answering System for Applicant Support Using Modern Messaging Apps

There is an increasing user interest in instant messaging applications. These applications allow us to interact with other users and include a functionality that can help us to implement bots that automate various business processes or provide information services. This paper considers a specialized question answering system that employs today’s messaging services infrastructure to support university applicants. Over two years, we gathered a corpus of typical questions of applicants and developed an information retrieval model for finding similar questions in this corpus. Applicants can type their questions using natural language without any formal requirements to phrase construction or using special templates. If the system is unable to find a relevant answer, the user can directly address the question to representatives of the university. The system was implemented using modern cloud services provided by Amazon. We used serverless computations and NoSQL databases, so we had to develop an appropriate architecture of the service. Since the system operates sensitive personal data and provides personalized service, we analyzed methods of ensuring system security and approaches to user authorization. We are currently testing our system and estimating its information retrieval quality.

Incremental author name disambiguation using author profile models and self-citations

Author name ambiguity in bibliographic databases (BDs) such as DBLP is a challenging problem that degrades the information retrieval quality, citation analysis, and proper attribution to the authors. It occurs when several authors have the same name (homonym) or when an author publishes under several name variants (synonym). Traditionally, much research has been conducted to disambiguate whole bibliographic database at once whenever some new citations are added in these BDs. However, it is more time-consuming and discards the manual disambiguation effects (if any). Only a few incremental author name disambiguation methods are proposed but these methods produce fragmented clusters which lower their accuracy. In this paper, a method, called CAND, that uses author profile models and self-citations for incremental author name disambiguation is proposed. CAND introduces name indices that enhance the overall system response by comparing the newly inserted references to the indexed author clusters. Author profile models are generated for the existing authors in BDs which help in disambiguating the newly inserted references. A comparator function is proposed to resolve the incremental author name ambiguity which utilizes the most strong bibliometric features such as coauthor, titles, author profile models, and self-citations. Two real-world data sets, one from Arnetminer and the other from BDBComp, are used to validate CAND's performance. Experimental results show that CAND's performance is overall better than the existing state-of-the-art incremental author name disambiguation methods.

Aspectos relevantes da arquivística contemporânea no âmbito da organização do conhecimento no Brasil

O objetivo do estudo é identificar elementos teórico-práticos de Arquivística presentes no âmbito da produção cientifica em Organização e Representação do Conhecimento no Brasil por meio de uma análise dos Anais da ISKO Brasil entre 2011 e 2017. O estudo justifica-se pelas possibilidades de avanço tanto teórico-práticos das aproximações conceituais e metodológicas entre a Arquivística e a ORIC em vista da melhoria da qualidade da recuperação da informação. O levantamento identificou uma presença crescente de temas de processamento técnico em Arquivística na dimensão Aplicada e uma escassez de abordagens na dimensão Epistemológica e Social.

Implications of inflationary trends on collection development at the University of Ilorin Library, 1976-1985, 2010-2014

This case study discussed inflation and its implication for collection development at the University of Ilorin Library in particular and academic Libraries in Nigeria. Documentary Research Method and Structured Oral Interview techniques were used to examine the records of budgetary allocations and expenditure in the acquisition of books and journals at the University of Ilorin Library between 2010 and 2014. The study identified some problems facing collection development at the university of Ilorin library as a result of inflationary trends. The study therefore posited that inflation-driven library collection development poses great danger to the quality of information resources of the library, the quality of information retrieval by library users, the quality of research and community service mantra of the university. It there recommended that collection development librarian should ensure balanced acquisition with the available funds. Rising number of academic programmes should be controlled in view of the fact that paucity of funds would not be able to go round the myriads of academic programmes satisfactorily. The Federal Government of Nigeria should checkmate inflationary phenomenon on library books and periodicals while textbook writers and publishers should focus more on producing local books/periodicals so that libraries and library clientele would be discouraged from patronizing the more expensive foreign publications.Keywords: Inflation, Collection Development, University of Ilorin, budgetary allocation

Question Answering System for Applicant Support by Using Modern Messengers

There is an increasing interest to the instant messaging applications, messengers. These applications allow us to interact with other users and include a functionality that can help us to implement bots that automate various business processes or provide information services. In this paper, we consider a specialized question answering system that uses today’s messaging services infrastructure to support university applicants. We gathered a corpus of applicants questions throughout two years and developed an information retrieval model that helps us to find similar questions in the corpus. Applicants can type their questions using a natural language without any formal requirements to phrase construction or using special templates. If the system is unable to find a relevant answer, the user can directly address the question to representatives of the university. The system was implemented with the use of modern cloud services that are provided by Amazon. We used serverless computations and NoSQL data bases, so we had to develop an architecture of the system in that way. Since the system contains sensitive personal data and provide personalized service, we must focus our attention on security. We proposed the means that must improve the safety of the system, more specifically, authentification process that can be used without the explicit use of personal data, however, this is a future work. At present we test our system and evaluate its quality of information retrieval.

Author Name Disambiguation by Exploiting Graph Structural Clustering and Hybrid Similarity

Author name ambiguity occurs when multiple authors share a common name and an author writes one’s name in many ways. This hinders the quality of information retrieval and correct attribution to authors in bibliographic databases. Despite much research in the past decade, the author name ambiguity problem remains largely unsolved. Outstanding issues include limited capabilities (solve only homonyms or synonyms), require extra information (Web or user feedback), actual number of authors K in advance and not scalable. In this paper, a method called GCLUSIM is proposed which uses graph structural clustering and proposed similarity measure to resolve ambiguous authors. GCLUSIM preprocesses citation data set and constructs co-authors graph. Graph-based structural clustering is applied to the constructed graph to identify hub nodes, outliers, and clusters of nodes. It resolves homonyms by splitting these clusters if the feature vector similarity between these clusters is less than the predefined threshold and synonyms by exploiting proposed similarity. Finally, it disambiguates sole authors by comparing name and feature vector similarities with the disambiguated clusters. Experiments are performed with Arnetminer and BDBComp to validate the performance of the GCLUSIM. Results show that GCLUSIM is scalable, overall better in performance than baselines and the number of clusters found is close to the ground truth clusters.

Detecting redirection spam using multilayer perceptron neural network

Quality information retrieval from Web is essential for every search engine. But the quality of information is being exploited by spammers who make heavy use of malicious redirections for the purpose of phishing, downloading malware or attaining high search engine ranking. Malicious redirections present the irrelevant content to search user, thereby affecting user satisfaction. It also leads to wastage of network bandwidth. In this paper, we propose a neural framework for detecting redirection spam. We incorporated the feed-forward multilayer perceptron network and used scaled conjugate gradient algorithm that is able to perform very fast classification of URLs leading to redirection spam. We investigated the network empirically to choose the number of hidden layers and observed that when network is trained with two hidden layers, it gives better accuracy. We validated our proposed approach against the dataset of 2383 URLs and were able to detect the spammed redirections with high accuracy. The results indicate that neural networks are very effective technique to model the redirection spam detection.

Willingness of patrons to use library public computing facilities: insights from Malaysia

Purpose This paper aims to examine relationships between attitude, self-efficacy and subjective norm with library patrons’ behavioural intention to use public computing facilities at a library. Design/methodology/approach Data were collected from 200 undergraduate students enrolled at a higher learning institution in the Federal Territory of Labuan, Malaysia, via a structured questionnaire comprising closed-ended questions. A structural equation modelling technique using Analysis of Moment Structures (AMOS) computer software version 21 was used to examine the stability of the model with the data and to estimate impacts among factors instantaneously. Findings The results show that library patrons’ behavioral intention to use public computing facilities at the library is widely affected by subjective norm factor, i.e. influence of the support of family members, friends and neighbours. Using public computers in a library helps them to be more independent in completing their assignments and conducting research collaboration, checking email messages, social networking and performing other online tasks. Practical implications The findings of this study provide a better understanding of factors likely to influence library patrons’ behavioral intention to use public computing facilities at a library. It also offers valuable insights into factors which university librarians need to focus on to improve library patrons’ behavioral intention to actively use public computing facilities at a library for quality information retrieval. Originality/value This study replaces perceived behavioral control with self-efficacy in the framework, as it overlaps with the concept of self-efficacy to provide more variance in behavioral intention to use public computing facilities at a library, which has been marginally researched in the Malaysian context.

Design and prototype of an interoperable online air quality information system

This paper focuses on the design and development of a Spatial Data Infrastructure (SDI)-compliant online system for air quality information retrieval, including support for real-time monitoring. This system assesses exposure to ambient air to mitigate potential health risks, which is crucial for susceptible individuals, health practitioners and decision makers. Particular attention is paid to the development of an interoperable, applicable and transferrable approach to the application of robust and flexible air quality modeling as required for early warning systems on the Web. Moreover, the design provides different access levels to system components for both non-expert and scientific users and supports extension with external standard compliant services. The developed Web-client Time2Maps enables the user to view, analyze and download requested air quality information and serves as a portal to the designed online system.

Improving the Efficiency of Term Weighting in Set of Dynamic Documents

In real information systems, there are few static documents. On the other hand, there are too many documents that their content change during the time that could be considered as signals to improve the quality of information retrieval. Unfortunately, considering all these changes could be time-consuming. In this paper, a method has been proposed that the time of analyzing these changes could be reduced significantly. The main idea of this method is choosing a special part of changes that do not make effective changes in the quality of information retrieval; but it could be possible to reduce the analyzing time. To evaluate the proposed method, three different datasets selected from Wikipedia. Different factors have been assessed in term weighting and the effect of the proposed method investigated on these factors. The results of empirical experiments showed that the proposed method could keep the quality of retrieved information in an acceptable rate and reduce the documents‘ analysis time as a result.

Semantic Web Improved with the Weighted IDF Feature

The development of search engines is taking at a very fast rate. A lot of algorithms have been tried and tested. But, still the people are not getting precise results. Social networking sites are developing at tremendous rate and their growth has given birth to the new interesting problems. The social networking sites use semantic data to enhance the results. This provides us with a new perspective on how to improve the quality of information retrieval. As we are aware, many techniques of text classification are based on TFIDF algorithm. Term weighting has a significant role in classifying a text document. In this paper, firstly, we are extending the queries by keyword+tags instead of keywords only. In addition to this, secondly, we have developed a new ranking algorithm (JEKS algorithm) based on semantic tags from user feedback that uses CiteUlike data. The algorithm enhances the already existing semantic web by using the weighted IDF feature of the TFIDF algorithm. The suggested algorithm provides a better ranking than Google and can be viewed as a semantic web service in the domain of academics.

Experimental performance evaluation of using multiset metrics in information retrieval problems

The problem of the comparative experimental performance evaluation using multiset metrics in information retrieval problems is considered in the paper. The main purpose of the studies is to prove on the basis of actual experimental data, the feasibility of using multisets, as a fundamentally new mathematical tool, in information retrieval problems. As a result of the preliminary statistical analysis of the available data set ‘’Anonymouswebdatafromwww.microsoft.com’’, specific features and problems of information search in the Internet space are identified. As the main performance indicator of information retrieval the “half-life of usefulness”, which predicts the user the usefulness of a list of recommended facilities, taking into account the user’s partial view of a list of recommendations, is used. The calculated values of the performance indicator of information retrieval are compared with the results of similar studies on the effectiveness of traditional, alternative methods of information retrieval. It is shown that the use of metric multisets in information retrieval problems improves the quality of information retrieval

Utilization of ontology look-up services in information retrieval for biomedical literature.

With the vast amount of biomedical data we face the necessity to improve information retrieval processes in biomedical domain. The use of biomedical ontologies facilitated the combination of various data sources (e.g. scientific literature, clinical data repository) by increasing the quality of information retrieval and reducing the maintenance efforts. In this context, we developed Ontology Look-up services (OLS), based on NEWT and MeSH vocabularies. Our services were involved in some information retrieval tasks such as gene/disease normalization. The implementation of OLS services significantly accelerated the extraction of particular biomedical facts by structuring and enriching the data context. The results of precision in normalization tasks were boosted on about 20%.

A Distributed N-Gram Indexing System to Optimizing Persian Information Retrieval

As the amount of information and the number of queries has been increasing today, indexing is a good solution to fight with the inherent complexity of text retrieval and accelerating information retrieval in different languages. Also N-Gram Indexing is a solution of the issues such as stemming, misspellings, multilingual and partial matching and has the advantages of language independent and error endurance. Persian is a name of a language which is common in the Middle East. It is spoken in some countries like Iran, Afghanistan and Tajikistan. Therefore, Persian is the language of many documents is published on the net. But, not more researches have been done about the Persian documents retrieval. In this paper, we present a method for Persian documents retrieving using N-gram indexing and distribution technique. The proposed index is a method of more effective answering queries that increases the quality of information retrieval substantially and we gain more optimizing retrieval in Persian documents. But the speed of N-gram indexing is low; to solve this problem we design a distributed N-gram indexing mechanism for large systems of Persian language. Compare with the other methods in this field, we improve the quality of retrieved documents and also the speed of information retrieval.

A balanced memory-based collaborative filtering similarity measure

Collaborative filtering recommender systems contribute to alleviating the problem of information overload that exists on the Internet as a result of the mass use of Web 2.0 applications. The use of an adequate similarity measure becomes a determining factor in the quality of the prediction and recommendation results of the recommender system, as well as in its performance. In this paper, we present a memory-based collaborative filtering similarity measure that provides extremely high-quality and balanced results; these results are complemented with a low processing time (high performance), similar to the one required to execute traditional similarity metrics. The experiments have been carried out on the MovieLens and Netflix databases, using a representative set of information retrieval quality measures. © 2012 Wiley Periodicals, Inc. © 2012 Wiley Periodicals, Inc.