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Article
Publication date: 3 June 2019

Bilal Hawashin, Shadi Alzubi, Tarek Kanan and Ayman Mansour

This paper aims to propose a new efficient semantic recommender method for Arabic content.

Abstract

Purpose

This paper aims to propose a new efficient semantic recommender method for Arabic content.

Design/methodology/approach

Three semantic similarities were proposed to be integrated with the recommender system to improve its ability to recommend based on the semantic aspect. The proposed similarities are CHI-based semantic similarity, singular value decomposition (SVD)-based semantic similarity and Arabic WordNet-based semantic similarity. These similarities were compared with the existing similarities used by recommender systems from the literature.

Findings

Experiments show that the proposed semantic method using CHI-based similarity and using SVD-based similarity are more efficient than the existing methods on Arabic text in term of accuracy and execution time.

Originality/value

Although many previous works proposed recommender system methods for English text, very few works concentrated on Arabic Text. The field of Arabic Recommender Systems is largely understudied in the literature. Aside from this, there is a vital need to consider the semantic relationships behind user preferences to improve the accuracy of the recommendations. The contributions of this work are the following. First, as many recommender methods were proposed for English text and have never been tested on Arabic text, this work compares the performance of these widely used methods on Arabic text. Second, it proposes a novel semantic recommender method for Arabic text. As this method uses semantic similarity, three novel base semantic similarities were proposed and evaluated. Third, this work would direct the attention to more studies in this understudied topic in the literature.

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Article
Publication date: 11 July 2019

Manjula Wijewickrema, Vivien Petras and Naomal Dias

The purpose of this paper is to develop a journal recommender system, which compares the content similarities between a manuscript and the existing journal articles in two…

Abstract

Purpose

The purpose of this paper is to develop a journal recommender system, which compares the content similarities between a manuscript and the existing journal articles in two subject corpora (covering the social sciences and medicine). The study examines the appropriateness of three text similarity measures and the impact of numerous aspects of corpus documents on system performance.

Design/methodology/approach

Implemented three similarity measures one at a time on a journal recommender system with two separate journal corpora. Two distinct samples of test abstracts were classified and evaluated based on the normalized discounted cumulative gain.

Findings

The BM25 similarity measure outperforms both the cosine and unigram language similarity measures overall. The unigram language measure shows the lowest performance. The performance results are significantly different between each pair of similarity measures, while the BM25 and cosine similarity measures are moderately correlated. The cosine similarity achieves better performance for subjects with higher density of technical vocabulary and shorter corpus documents. Moreover, increasing the number of corpus journals in the domain of social sciences achieved better performance for cosine similarity and BM25.

Originality/value

This is the first work related to comparing the suitability of a number of string-based similarity measures with distinct corpora for journal recommender systems.

Details

The Electronic Library , vol. 37 no. 3
Type: Research Article
ISSN: 0264-0473

Keywords

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Article
Publication date: 1 June 2010

Ulrich Herb, Eva Kranz, Tobias Leidinger and Björn Mittelsdorf

Usually the impact of research and researchers is quantified by using citation data: either by journal‐centered citation data as in the case of the journal impact factor…

Abstract

Purpose

Usually the impact of research and researchers is quantified by using citation data: either by journal‐centered citation data as in the case of the journal impact factor (JIF) or by author‐centered citation data as in the case of the Hirsch‐ or h‐index. This paper aims to discuss a range of impact measures, especially usage‐based metrics, and to report the results of two surveys.

Design/methodology/approach

The first part of the article analyzes both citation‐based and usage‐based metrics. The second part is based on the findings of the surveys: one in the form of a brainstorming session with information professionals and scientists at the OAI6 conference in Geneva, the second in the form of expert interviews, mainly with scientists.

Findings

The results of the surveys indicate an interest in the social aspects of science, like visualizations of social graphs both for persons and their publications. Furthermore, usage data are considered an appropriate measure to describe quality and coverage of scientific documents; admittedly, the consistence of usage information among repositories has to be kept in mind. The scientists who took part in the survey also asked for community services, assuming these might help to identify relevant scientific information more easily. Some of the other topics of interest were personalization or easy submission procedures.

Originality/value

This paper delineates current discussions about citation‐based and usage‐based metrics. Based on the results of the surveys, it depicts which functionalities could enhance repositories, what features are required by scientists and information professionals, and whether usage‐based services are considered valuable. These results also outline some elements of future repository research.

Details

OCLC Systems & Services: International digital library perspectives, vol. 26 no. 2
Type: Research Article
ISSN: 1065-075X

Keywords

Content available
Article
Publication date: 5 June 2009

Abstract

Details

Library Hi Tech News, vol. 26 no. 5/6
Type: Research Article
ISSN: 0741-9058

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Article
Publication date: 22 September 2020

Arghya Ray, Pradip Kumar Bala and Rashmi Jain

Social media channels provide an avenue for expressing views about different services/products. However, unlike merchandise/company websites (where users can post both…

Abstract

Purpose

Social media channels provide an avenue for expressing views about different services/products. However, unlike merchandise/company websites (where users can post both reviews and ratings), it is not possible to understand user's ratings for a particular service-related comment on social media unless explicitly mentioned. Predicting ratings can be beneficial for service providers and prospective customers. Additionally, predicting ratings from a user-generated content can help in developing vast data sets for recommender systems utilizing recent data. The aim of this study is to predict ratings more accurately and enhance the performance of sentiment-based predictors by combining it with the emotional content of textual data.

Design/methodology/approach

This study had utilized a combination of sentiment and emotion scores to predict the ratings of Twitter posts (3,509 tweets) in three different contexts, namely, online food delivery (OFD) services, online travel agencies (OTAs) and online learning (e-learning). A total of 29,551 reviews were utilized for training and testing purposes.

Findings

Results of this study indicate accuracies of 58.34%, 57.84% and 100% in cases of e-learning, OTA and OFD services, respectively. The combination of sentiment and emotion scores showed an increase in accuracies of 19.41%, 27.83% and 40.20% in cases of e-learning, OFD and OTA services, respectively.

Practical implications

Understanding the ratings of social media comments can help both service providers as well as prospective customers who do not spend much time reading posts but want to understand the perspectives of others about a particular service/product. Additionally, predicting ratings of social media comments will help to build databases for recommender systems in different contexts.

Originality/value

The uniqueness of this study is in utilizing a combination of sentiment and emotion scores to predict the ratings of tweets related to different online services, namely, e-learning OFD and OTAs.

Details

Benchmarking: An International Journal, vol. 28 no. 2
Type: Research Article
ISSN: 1463-5771

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Article
Publication date: 21 October 2019

Priyadarshini R., Latha Tamilselvan and Rajendran N.

The purpose of this paper is to propose a fourfold semantic similarity that results in more accuracy compared to the existing literature. The change detection in the URL…

Abstract

Purpose

The purpose of this paper is to propose a fourfold semantic similarity that results in more accuracy compared to the existing literature. The change detection in the URL and the recommendation of the source documents is facilitated by means of a framework in which the fourfold semantic similarity is implied. The latest trends in technology emerge with the continuous growth of resources on the collaborative web. This interactive and collaborative web pretense big challenges in recent technologies like cloud and big data.

Design/methodology/approach

The enormous growth of resources should be accessed in a more efficient manner, and this requires clustering and classification techniques. The resources on the web are described in a more meaningful manner.

Findings

It can be descripted in the form of metadata that is constituted by resource description framework (RDF). Fourfold similarity is proposed compared to three-fold similarity proposed in the existing literature. The fourfold similarity includes the semantic annotation based on the named entity recognition in the user interface, domain-based concept matching and improvised score-based classification of domain-based concept matching based on ontology, sequence-based word sensing algorithm and RDF-based updating of triples. The aggregation of all these similarity measures including the components such as semantic user interface, semantic clustering, and sequence-based classification and semantic recommendation system with RDF updating in change detection.

Research limitations/implications

The existing work suggests that linking resources semantically increases the retrieving and searching ability. Previous literature shows that keywords can be used to retrieve linked information from the article to determine the similarity between the documents using semantic analysis.

Practical implications

These traditional systems also lack in scalability and efficiency issues. The proposed study is to design a model that pulls and prioritizes knowledge-based content from the Hadoop distributed framework. This study also proposes the Hadoop-based pruning system and recommendation system.

Social implications

The pruning system gives an alert about the dynamic changes in the article (virtual document). The changes in the document are automatically updated in the RDF document. This helps in semantic matching and retrieval of the most relevant source with the virtual document.

Originality/value

The recommendation and detection of changes in the blogs are performed semantically using n-triples and automated data structures. User-focussed and choice-based crawling that is proposed in this system also assists the collaborative filtering. Consecutively collaborative filtering recommends the user focussed source documents. The entire clustering and retrieval system is deployed in multi-node Hadoop in the Amazon AWS environment and graphs are plotted and analyzed.

Details

International Journal of Intelligent Unmanned Systems, vol. 7 no. 4
Type: Research Article
ISSN: 2049-6427

Keywords

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Article
Publication date: 4 September 2009

Michael Schuricht, Zachary Davis, Michael Hu, Shreyas Prasad, Peter M. Melliar‐Smith and Louise E. Moser

Mobile handheld devices, such as cellular phones and personal digital assistants, are inherently small and lack an intuitive and natural user interface. Speech recognition…

Abstract

Purpose

Mobile handheld devices, such as cellular phones and personal digital assistants, are inherently small and lack an intuitive and natural user interface. Speech recognition and synthesis technology can be used in mobile handheld devices to improve the user experience. The purpose of this paper is to describe a prototype system that supports multiple speech‐enabled applications in a mobile handheld device.

Design/methodology/approach

The main component of the system, the Program Manager, coordinates and controls the speech‐enabled applications. Human speech requests to, and responses from, these applications are processed in the mobile handheld device, to achieve the goal of human‐like interactions between the human and the device. In addition to speech, the system also supports graphics and text, i.e., multimodal input and output, for greater usability, flexibility, adaptivity, accuracy, and robustness. The paper presents a qualitative and quantitative evaluation of the prototype system. The Program Manager is currently designed to handle the specific speech‐enabled applications that we developed.

Findings

The paper determines that many human interactions involve not single applications but multiple applications working together in possibly unanticipated ways.

Research limitations/implications

Future work includes generalization of the Program Manager so that it supports arbitrary applications and the addition of new applications dynamically. Future work also includes deployment of the Program Manager and the applications on cellular phones running the Android Platform or the Openmoko Framework.

Originality/value

This paper presents a first step towards a future human interface for mobile handheld devices and for speech‐enabled applications operating on those devices.

Details

International Journal of Pervasive Computing and Communications, vol. 5 no. 3
Type: Research Article
ISSN: 1742-7371

Keywords

Content available
Article
Publication date: 3 September 2019

Amal S.A. Shurair and Shaligram Pokharel

The purpose of this paper is to investigate and report students’ perception of service quality in a university by examining the perceptual context of service quality with…

Abstract

Purpose

The purpose of this paper is to investigate and report students’ perception of service quality in a university by examining the perceptual context of service quality with respect to students’ loyalty behavior, image of the university and culture/values.

Design/methodology/approach

A research framework is developed for quality assessment with three hypotheses. A questionnaire with 65 instruments was used for gathering the required data for the analysis. The questionnaire was sent through email to all engineering students. The analysis included descriptive statistics, reliability analysis, gap analysis and hypotheses tests. Seven dimensions of service quality were identified: the original dimensions of the SERVQUAL, namely, reliability, responsiveness, assurance, empathy and tangibles. Two additional dimensions image and culture/value were added for the research to understand perceived service quality and loyalty.

Findings

The results provide a significant positive correlation between service quality and student's loyalty. It also shows that there is statistically significant relation between the image of the institution and the perceived service quality, and culture/values of the students in the institution and perceived service quality.

Research limitations/implications

This study used data collected from a survey in the university in a given period.

Practical implications

The findings indicate that to provide quality education, meeting students’ needs, wants and expectations of services quality should be carefully understood and addressed. Management also needs to consider factors such as corporate image and culture/value, as they have the ability to heavily impact the type of services provided by the institution.

Originality/value

The findings presented in this paper fill the gap in the current literature by providing empirical knowledge on the quality of service assessment and customer satisfaction in the higher education context. The study is the first of its kind in Qatar’s context and provides opportunities for higher institutions to focus more on current students’ services. This can lead to an increased brand value representing one of the premier institutes of higher education in the Middle East Gulf Region.

Details

Quality Assurance in Education, vol. 27 no. 4
Type: Research Article
ISSN: 0968-4883

Keywords

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Abstract

Details

Organizational Behavior Management
Type: Book
ISBN: 978-1-78769-678-5

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Article
Publication date: 3 June 2019

Tibor Mandják, Samy Belaid and Peter Naudé

The purpose of this paper is to empirically investigate how context influences the quality of business relationships. This theoretical question is studied from the point…

Abstract

Purpose

The purpose of this paper is to empirically investigate how context influences the quality of business relationships. This theoretical question is studied from the point of view of trust, one of the important components of business relationship quality. The authors study how trust is related to the dynamics and management of the business relationship in the context of an emerging market.

Design/methodology/approach

This paper is based on qualitative interviews with 15 spare-parts resellers in the Tunisian automotive industry. The authors take a monadic view, interviewing resellers about their relationships with their wholesalers-importers. The decision to undertake the research in Tunisia is based on three factors. First, Tunisia is an emerging country and there is very little published research based in the Maghreb countries. Second, the Tunisian automotive parts market structure is relatively simple and, hence, easily understood, with most spare-parts being imported because of the low level of local production. Third, the actors in the study are all Tunisian companies, so research allows us to explore relationships between local companies in an emerging country.

Findings

The authors find that different kinds of trust play different roles over the dynamics of the relationship. Perceived trust is more important at the emergent stage of a relationship, and as the two parties learn from each other, experienced trust becomes more important in the established relationships. The initial perceived trust creates the possibility of building trust, and when mutual trust exists between the parties, it motivates them to maintain the relationship, but there is always the threat of the degradation of the quality of the relationship because of the violation or destruction of the trust.

Research limitations/implications

This paper shows that more care should be taken when using trust as the variable under scrutiny. Different aspects of trust manifest themselves at various stages of the relationship building cycle.

Practical implications

The results emphasize that when initiating a business relationship, managers first need to create perceived trust. Thereafter, once trust is built up, it is the trust that may “manage” or act to control the on-going relationship as long as the partners’ behavior or network changes do not violate the trust.

Originality/value

The results of this paper show that there is a mutual but not necessarily symmetrical or balanced influence of trust on the behavior of the partners involved. The influence of the different parties is dependent on the power architecture, the history of the relationship and the network position of the actors.

Details

Journal of Business & Industrial Marketing, vol. 34 no. 6
Type: Research Article
ISSN: 0885-8624

Keywords

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