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Article

S. Thenmalar and T.V. Geetha

The purpose of this paper is to improve the conceptual-based search by incorporating structural ontological information such as concepts and relations. Generally…

Abstract

Purpose

The purpose of this paper is to improve the conceptual-based search by incorporating structural ontological information such as concepts and relations. Generally, Semantic-based information retrieval aims to identify relevant information based on the meanings of the query terms or on the context of the terms and the performance of semantic information retrieval is carried out through standard measures-precision and recall. Higher precision leads to the (meaningful) relevant documents obtained and lower recall leads to the less coverage of the concepts.

Design/methodology/approach

In this paper, the authors enhance the existing ontology-based indexing proposed by Kohler et al., by incorporating sibling information to the index. The index designed by Kohler et al., contains only super and sub-concepts from the ontology. In addition, in our approach, we focus on two tasks; query expansion and ranking of the expanded queries, to improve the efficiency of the ontology-based search. The aforementioned tasks make use of ontological concepts, and relations existing between those concepts so as to obtain semantically more relevant search results for a given query.

Findings

The proposed ontology-based indexing technique is investigated by analysing the coverage of concepts that are being populated in the index. Here, we introduce a new measure called index enhancement measure, to estimate the coverage of ontological concepts being indexed. We have evaluated the ontology-based search for the tourism domain with the tourism documents and tourism-specific ontology. The comparison of search results based on the use of ontology “with and without query expansion” is examined to estimate the efficiency of the proposed query expansion task. The ranking is compared with the ORank system to evaluate the performance of our ontology-based search. From these analyses, the ontology-based search results shows better recall when compared to the other concept-based search systems. The mean average precision of the ontology-based search is found to be 0.79 and the recall is found to be 0.65, the ORank system has the mean average precision of 0.62 and the recall is found to be 0.51, while the concept-based search has the mean average precision of 0.56 and the recall is found to be 0.42.

Practical implications

When the concept is not present in the domain-specific ontology, the concept cannot be indexed. When the given query term is not available in the ontology then the term-based results are retrieved.

Originality/value

In addition to super and sub-concepts, we incorporate the concepts present in same level (siblings) to the ontological index. The structural information from the ontology is determined for the query expansion. The ranking of the documents depends on the type of the query (single concept query, multiple concept queries and concept with relation queries) and the ontological relations that exists in the query and the documents. With this ontological structural information, the search results showed us better coverage of concepts with respect to the query.

Details

Aslib Journal of Information Management, vol. 66 no. 6
Type: Research Article
ISSN: 2050-3806

Keywords

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Article

Somu Renugadevi, T.V. Geetha, R.L. Gayathiri, S. Prathyusha and T. Kaviya

The purpose of this paper is to propose the Collaborative Search System that attempts to achieve collaboration by implicitly identifying and reflecting search behaviour of…

Abstract

Purpose

The purpose of this paper is to propose the Collaborative Search System that attempts to achieve collaboration by implicitly identifying and reflecting search behaviour of collaborators in an academic network that is automatically and dynamically formed. By using the constructed Collaborative Hit Matrix (CHM), results are obtained that are based on the search behaviour and earned preferences of specialist communities of researchers, which are relevant to the user's need and reduce the time spent on bad links.

Design/methodology/approach

By using the Digital Bibliography Library Project (DBLP), the research communities are formed implicitly and dynamically based on the users’ research presence in the search environment and in the publication scenario, which is also used to assign users’ roles and establish links between the users. The CHM, to store the hit count and hit list of page results for queries, is also constructed and updated after every search session to enhance the collaborative search among the researchers.

Findings

The implicit researchers community formation, the assignment and dynamic updating of roles of the researchers based on research, search presence and search behaviour on the web as well as the usage of these roles during Collaborative Web Search have highly improved the relevancy of results. The CHM that holds the collaborative responses provided by the researchers on the search query results to support searching distinguishes this system from others. Thus the proposed system considerably improves the relevancy and reduces the time spent on bad links, thus improving recall and precision.

Originality/value

The research findings illustrate the better performance of the system, by connecting researchers working in the same field and allowing them to help each other in a web search environment.

Details

Aslib Journal of Information Management, vol. 66 no. 5
Type: Research Article
ISSN: 2050-3806

Keywords

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Article

I‐En Liao, Wen‐Chiao Hsu, Ming‐Shen Cheng and Li‐Ping Chen

The purpose of this paper is not only to design a more effective recommendation system for libraries, but also to eliminate many of the weaknesses found in the existing…

Abstract

Purpose

The purpose of this paper is not only to design a more effective recommendation system for libraries, but also to eliminate many of the weaknesses found in the existing library recommender systems.

Design/methodology/approach

A novel library recommender system was designed for English collections by integrating personal ontology model and collaborative filtering model with domain specification.

Findings

The trend of the traditional library is evolving toward that of digital library. The personal ontology recommender (PORE) system offers a friendly user interface and provides several personalized services.

Research limitations/implications

This system is only implemented and tested in the Library of National Chung Hsing University in Taiwan.

Originality/value

The paper demonstrates a good methodology to offer an active, effective, and personalized recommendation system for library patrons.

Details

The Electronic Library, vol. 28 no. 3
Type: Research Article
ISSN: 0264-0473

Keywords

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Article

Asela Indunil Gunesekera, Yukun Bao and Mboni Kibelloh

The purpose of this study is to review the effect of usability factors on e-learning user relationships, namely, student–student interaction (SSI), student–instructor…

Abstract

Purpose

The purpose of this study is to review the effect of usability factors on e-learning user relationships, namely, student–student interaction (SSI), student–instructor interaction (SII) and student–content interaction (SCI), in the existing e-learning literature. Further, this study intended to identify whether usability contributes to the satisfaction of e-learners.

Design/methodology/approach

This study has undertaken a systematic review using the PRISMA methodology to filter the literature in the domain of e-learning with respect to usability concerns using six databases. An analytical framework has been formulated to evaluate the literature against different dimensions of interactions and usability.

Findings

Results reveal that while SSI has grabbed 71.4 per cent research attention with respect to usability factors of e-learning systems, SCI has been given the least focus, i.e. 26.6 per cent. According to the results, e-learning systems’ usability issues influence the user relationships and affect the user satisfaction, which will lead to lack of user continuity.

Practical implications

The findings of this review will provide insights to instructional designers to construct more satisfied learning content for the users. The analysis framework of this study will encourage researchers to drive future research in e-learning along with the concern of usability.

Originality/value

This research emphasizes on the importance of SCI to focus future e-learning research on a different angle, in addition to SSI and SII. The analysis framework of this study will provide different dimensions, specifically for the empirical research in the domain of e-learning.

Details

Journal of Systems and Information Technology, vol. 21 no. 3
Type: Research Article
ISSN: 1328-7265

Keywords

Content available
Article

Paramita Ray and Amlan Chakrabarti

Social networks have changed the communication patterns significantly. Information available from different social networking sites can be well utilized for the analysis…

Abstract

Social networks have changed the communication patterns significantly. Information available from different social networking sites can be well utilized for the analysis of users opinion. Hence, the organizations would benefit through the development of a platform, which can analyze public sentiments in the social media about their products and services to provide a value addition in their business process. Over the last few years, deep learning is very popular in the areas of image classification, speech recognition, etc. However, research on the use of deep learning method in sentiment analysis is limited. It has been observed that in some cases the existing machine learning methods for sentiment analysis fail to extract some implicit aspects and might not be very useful. Therefore, we propose a deep learning approach for aspect extraction from text and analysis of users sentiment corresponding to the aspect. A seven layer deep convolutional neural network (CNN) is used to tag each aspect in the opinionated sentences. We have combined deep learning approach with a set of rule-based approach to improve the performance of aspect extraction method as well as sentiment scoring method. We have also tried to improve the existing rule-based approach of aspect extraction by aspect categorization with a predefined set of aspect categories using clustering method and compared our proposed method with some of the state-of-the-art methods. It has been observed that the overall accuracy of our proposed method is 0.87 while that of the other state-of-the-art methods like modified rule-based method and CNN are 0.75 and 0.80 respectively. The overall accuracy of our proposed method shows an increment of 7–12% from that of the state-of-the-art methods.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

Keywords

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Article

Albert Alexander Stonier, Gnanavel Chinnaraj, Ramani Kannan and Geetha Mani

This paper aims to examine the design and control of a symmetric multilevel inverter (MLI) using grey wolf optimization and differential evolution algorithms.

Abstract

Purpose

This paper aims to examine the design and control of a symmetric multilevel inverter (MLI) using grey wolf optimization and differential evolution algorithms.

Design/methodology/approach

The optimal modulation index along with the switching angles are calculated for an 11 level inverter. Harmonics are used to estimate the quality of output voltage and measuring the improvement of the power quality.

Findings

The simulation is carried out in MATLAB/Simulink for 11 levels of symmetric MLI and compared with the conventional inverter design. A solar photovoltaic array-based experimental setup is considered to provide the input for symmetric MLI. Field Programmable Gate Array (FPGA) based controller is used to provide the switching pulses for the inverter switches.

Originality/value

Attempted to develop a system with different optimization techniques.

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Article

Chandra Shekher Purohit, Saibal Manna, Geetha Mani and Albert Alexander Stonier

This paper aims to deal with application of artificial intelligence for solving real time control complication adhered with the controlled operation of a buck power…

Abstract

Purpose

This paper aims to deal with application of artificial intelligence for solving real time control complication adhered with the controlled operation of a buck power converter. This type of converter finds application for power conversion at various levels for the direct current-direct current power industry to step down the input voltage.

Design/methodology/approach

Use of ANN-RL (Artificial Neural Networks- Reinforcement Learning)-based control algorithm to control buck power converter shows robustness against parameter and load variation. Because of non-linearity instigated by element used for switching, control of this converter becomes an arduous control predicament. All the classical control techniques are based on an approximate linear model of the step down converter and these techniques fail to handle actual non-linearity.

Findings

In this paper, a reinforcement learning-based algorithm has been used to handle and control buck power converter output voltage, without approximating the model of converter. The non-linearity instigated in converter is subjected to state of switch. Model of buck power converter is defined as a multi-step decision problem so that it can be solved using mathematical model of Markov decision process (MDP) and, in turn, reinforcement learning can be implemented. As MDP model is available for a discrete state system so model of converter has to be discretized and then value iteration is applied and output is analyzed. Load regulation and integral time absolute error analysis is done to show efficacy of this technique.

Originality/value

To mitigate the effect of discretization function approximation using neural network is applied. MATrix LABoratory has been used for implementation and result indicates an improvement in the overall response.

Details

Circuit World, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0305-6120

Keywords

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Article

Dan Wu, Shaobo Liang and Wenting Yu

The purpose of this paper is to explore users’ learning in the collaborative information search process when they conduct an academic task as a group.

Abstract

Purpose

The purpose of this paper is to explore users’ learning in the collaborative information search process when they conduct an academic task as a group.

Design/methodology/approach

This paper presents a longitudinal study for a three-month period on an actual task. The participants, who were undergraduate students, needed to write a research proposal in three months to apply for funding for a research project, including a three-hour experiment.

Findings

The results show that undergraduates’ learning in the collaborative search process for academic group work included knowledge reconstruction, tuning, and assimilation. Their understanding of the topic concepts improved through the process, and their attitudes became more optimistic. Besides, the learning in the collaborative information search process also enhanced participants’ skills in communication, research, information search, and collaboration. To improve learning outcomes, professional and appropriate academic resources are required, as well as effective division of labor, positive sharing behaviors, and use of collaborative systems.

Practical implications

The future development of collaborative information search systems should focus on the needs of academic research and support for elements such as instant communication and knowledge sharing.

Originality/value

This paper contributes to research into searching as learning by understanding undergraduates’ collaborative search behavior for writing a proposal.

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Article

Abu Hashan Md Mashud, Md. Rakibul Hasan, Hui Ming Wee and Yosef Daryanto

This paper aims to simultaneously consider an inventory model with price and advertisement dependent demand, non-instantaneous deterioration rate with preservation…

Abstract

Purpose

This paper aims to simultaneously consider an inventory model with price and advertisement dependent demand, non-instantaneous deterioration rate with preservation technology investment, partially backlogged shortages and trade credit.

Design/methodology/approach

This model considered a non-instantaneous deterioration, which starts after a certain storage period with a constant rate. The proposed model focused on two things. The first one is to reduce the deterioration rate by preservation technology investment, and the second one is using an appropriate trade credit period to maximize the total profit. The classical optimization technique is used to solve the problem.

Findings

The authors found that trade credit, advertising cost, preservation technology affect the total cost and selling price is one of the most important decision variables affecting the model.

Practical implications

This study provides a reference for a manufacturer and a retailer on making inventory decisions under different pricing, advertisement expense, preservation technology investment and credit strategies. Four cases are presented to illustrate the inventory model. Sensitivity analyses are performed to gain managerial insights for decision-making.

Originality/value

The study simultaneously considers a non-instantaneous deterioration inventory model, trade-credit, and preservation technology and advertisement policy. From our literature search, no researcher has undergone this type of study.

Abstract

Purpose

This paper aims to establish a more accurate model for lifetime estimation.

Design/methodology/approach

Finite element model simulation and experimental tests are used to enhance the lifetime prediction model of the solder joint.

Findings

A more precise model was found.

Originality/value

It is confirmed that the paper is original.

Details

Soldering & Surface Mount Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0954-0911

Keywords

1 – 10 of 126