Search results

1 – 10 of 98
Per page
102050
Citations:
Loading...
Access Restricted. View access options
Article
Publication date: 4 July 2023

Yuping Xing and Yongzhao Zhan

For ranking aggregation in crowdsourcing task, the key issue is how to select the optimal working group with a given number of workers to optimize the performance of their…

121

Abstract

Purpose

For ranking aggregation in crowdsourcing task, the key issue is how to select the optimal working group with a given number of workers to optimize the performance of their aggregation. Performance prediction for ranking aggregation can solve this issue effectively. However, the performance prediction effect for ranking aggregation varies greatly due to the different influencing factors selected. Although questions on why and how data fusion methods perform well have been thoroughly discussed in the past, there is a lack of insight about how to select influencing factors to predict the performance and how much can be improved of.

Design/methodology/approach

In this paper, performance prediction of multivariable linear regression based on the optimal influencing factors for ranking aggregation in crowdsourcing task is studied. An influencing factor optimization selection method based on stepwise regression (IFOS-SR) is proposed to screen the optimal influencing factors. A working group selection model based on the optimal influencing factors is built to select the optimal working group with a given number of workers.

Findings

The proposed approach can identify the optimal influencing factors of ranking aggregation, predict the aggregation performance more accurately than the state-of-the-art methods and select the optimal working group with a given number of workers.

Originality/value

To find out under which condition data fusion method may lead to performance improvement for ranking aggregation in crowdsourcing task, the optimal influencing factors are identified by the IFOS-SR method. This paper presents an analysis of the behavior of the linear combination method and the CombSUM method based on the optimal influencing factors, and optimizes the task assignment with a given number of workers by the optimal working group selection method.

Details

Data Technologies and Applications, vol. 58 no. 2
Type: Research Article
ISSN: 2514-9288

Keywords

Access Restricted. View access options
Article
Publication date: 28 September 2023

Jill Fenton Taylor and Ivana Crestani

This paper aims to explore how an academic researcher and a practitioner experience scepticism for their qualitative research.

170

Abstract

Purpose

This paper aims to explore how an academic researcher and a practitioner experience scepticism for their qualitative research.

Design/methodology/approach

The study applies Olt and Teman's new conceptual phenomenological polyethnography (2019) methodology, a hybrid of phenomenology and duoethnography.

Findings

For the researcher-participants, the essence of living with scepticism means feeling a sense of injustice; struggling with the desire for simplicity and quantification; being in a circle of uneasiness; having a survival mechanism; and embracing healthy scepticism. They experience the essence differently and similarly in varied cultural contexts. Through duoethnographic conversations, they acknowledge that while there can be scepticism of their work, it is important to remain sceptical, persistent and curious by challenging traditional concepts. Theoretical and practical advances in artificial intelligence (AI) continue to highlight the need for clarifying qualitative researcher roles in academia and practice.

Originality/value

This paper contributes to the debate of qualitative versus quantitative research. Its originality is in exploring scepticism as lived experience, from an academic and practitioner perspective and applying a phenomenological polyethnography approach that blends two different traditional research paradigms.

Access Restricted. View access options
Article
Publication date: 1 January 1995

F. CRESTANI and C.J. VAN RIJSBERGEN

The evaluation of an implication by Imaging is a logical technique developed in the framework of modal logic. Its interpretation in the context of a ‘possible worlds’ semantics is…

130

Abstract

The evaluation of an implication by Imaging is a logical technique developed in the framework of modal logic. Its interpretation in the context of a ‘possible worlds’ semantics is very appealing for ir. In 1989, Van Rijsbergen suggested its use for solving one of the fundamental problems of logical models of IR: the evaluation of the implication d → q (where d and q are respectively a document and a query representation). Since then, others have tried to follow that suggestion proposing models and applications, though without much success. Most of these approaches had as their basic assumption the consideration that ‘a document is a possible world’. We propose instead an approach based on a completely different assumption: ‘a term is a possible world’. This approach enables the exploitation of term‐term relationships which are estimated using an information theoretic measure.

Details

Journal of Documentation, vol. 51 no. 1
Type: Research Article
ISSN: 0022-0418

Access Restricted. View access options
Article
Publication date: 5 September 2018

Mengdi Li, Eugene Ch’ng, Alain Yee Loong Chong and Simon See

Recently, various Twitter Sentiment Analysis (TSA) techniques have been developed, but little has paid attention to the microblogging feature – emojis, and few works have been…

1502

Abstract

Purpose

Recently, various Twitter Sentiment Analysis (TSA) techniques have been developed, but little has paid attention to the microblogging feature – emojis, and few works have been conducted on the multi-class sentiment analysis of tweets. The purpose of this paper is to consider the popularity of emojis on Twitter and investigate the feasibility of an emoji training heuristic for multi-class sentiment classification of tweets. Tweets from the “2016 Orlando nightclub shooting” were used as a source of study. Besides, this study also aims to demonstrate how mapping can contribute to interpreting sentiments.

Design/methodology/approach

The authors presented a methodological framework to collect, pre-process, analyse and map public Twitter postings related to the shooting. The authors designed and implemented an emoji training heuristic, which automatically prepares the training data set, a feature needed in Big Data research. The authors improved upon the previous framework by advancing the pre-processing techniques, enhancing feature engineering and optimising the classification models. The authors constructed the sentiment model with a logistic regression classifier and selected features. Finally, the authors presented how to visualise citizen sentiments on maps dynamically using Mapbox.

Findings

The sentiment model constructed with the automatically annotated training sets using an emoji approach and selected features performs well in classifying tweets into five different sentiment classes, with a macro-averaged F-measure of 0.635, a macro-averaged accuracy of 0.689 and the MAEM of 0.530. Compared to those experimental results in related works, the results are satisfactory, indicating the model is effective and the proposed emoji training heuristic is useful and feasible in multi-class TSA. The maps authors created, provide a much easier-to-understand visual representation of the data, and make it more efficient to monitor citizen sentiments and distributions.

Originality/value

This work appears to be the first to conduct multi-class sentiment classification on Twitter with automatic annotation of training sets using emojis. Little attention has been paid to applying TSA to monitor the public’s attitudes towards terror attacks and country’s gun policies, the authors consider this work to be a pioneering work. Besides, the authors have introduced a new data set of 2016 Orlando Shooting tweets, which will be made available for other researchers to mine the public’s political opinions about gun policies.

Details

Industrial Management & Data Systems, vol. 118 no. 9
Type: Research Article
ISSN: 0263-5577

Keywords

Access Restricted. View access options
Book part
Publication date: 14 December 2017

Angelo Corallo, Fabrizio Errico, Laura Fortunato, Maria Elena Latino and Marta Menegoli

Following the triple helix (TH) model and the way knowledge is transferred into the industry domain, this chapter aims to define features interface that should be implemented in…

Abstract

Following the triple helix (TH) model and the way knowledge is transferred into the industry domain, this chapter aims to define features interface that should be implemented in order to facilitate the University–Industry (UI) relationship and thus encourage the spin-off creation.

In order to support this relationship, a new business model configuration of an entrepreneurial ecosystem is proposed, aiming at creating a sustainable environment, where business entities can grow. The field of the Governance of Entrepreneurial Ecosystems is also investigated in order to define a framework for launching, developing, and sustaining a company over time.

This chapter presents a case study developed within the University of Salento (Italy). It capitalizes results from three different research analyses, based on questionnaires and interviews with actors of the spin-off network (professors and researchers, graduating students, admin-tech staff of the Technology Transfer Office, spin-offs’ CEOs/Associates, and R&D managers of external companies) and on results coming from scientific publications and regional/national reports in the innovation context.

A research methodology based on semantic network analysis and sentiment analysis has been applied in order to identify which features an interface should implement in order to facilitate the UI relationship and encourage the spin-off creation.

To support the start-up overcoming the “death valley,” the creation of a link between the strategy used to transfer value to the market and the phase of innovation is proposed inside the business model configuration. Some aspects of a governance model of an entrepreneurial ecosystem were also presented in order to support the business evolution of a single business entity and assuring sustainability over time.

Details

Global Opportunities for Entrepreneurial Growth: Coopetition and Knowledge Dynamics within and across Firms
Type: Book
ISBN: 978-1-78714-502-3

Keywords

Access Restricted. View access options
Article
Publication date: 13 May 2020

Hengqin Wu, Geoffrey Shen, Xue Lin, Minglei Li, Boyu Zhang and Clyde Zhengdao Li

This study proposes an approach to solve the fundamental problem in using query-based methods (i.e. searching engines and patent retrieval tools) to screen patents of information…

638

Abstract

Purpose

This study proposes an approach to solve the fundamental problem in using query-based methods (i.e. searching engines and patent retrieval tools) to screen patents of information and communication technology in construction (ICTC). The fundamental problem is that ICTC incorporates various techniques and thus cannot be simply represented by man-made queries. To investigate this concern, this study develops a binary classifier by utilizing deep learning and NLP techniques to automatically identify whether a patent is relevant to ICTC, thus accurately screening a corpus of ICTC patents.

Design/methodology/approach

This study employs NLP techniques to convert the textual data of patents into numerical vectors. Then, a supervised deep learning model is developed to learn the relations between the input vectors and outputs.

Findings

The validation results indicate that (1) the proposed approach has a better performance in screening ICTC patents than traditional machine learning methods; (2) besides the United States Patent and Trademark Office (USPTO) that provides structured and well-written patents, the approach could also accurately screen patents form Derwent Innovations Index (DIX), in which patents are written in different genres.

Practical implications

This study contributes a specific collection for ICTC patents, which is not provided by the patent offices.

Social implications

The proposed approach contributes an alternative manner in gathering a corpus of patents for domains like ICTC that neither exists as a searchable classification in patent offices, nor is accurately represented by man-made queries.

Originality/value

A deep learning model with two layers of neurons is developed to learn the non-linear relations between the input features and outputs providing better performance than traditional machine learning models. This study uses advanced NLP techniques lemmatization and part-of-speech POS to process textual data of ICTC patents. This study contributes specific collection for ICTC patents which is not provided by the patent offices.

Details

Engineering, Construction and Architectural Management, vol. 27 no. 8
Type: Research Article
ISSN: 0969-9988

Keywords

Access Restricted. View access options
Article
Publication date: 26 April 2019

Jacqueline Sachse

Web search is more and more moving into mobile contexts. However, screen size of mobile devices is limited and search engine result pages face a trade-off between offering…

574

Abstract

Purpose

Web search is more and more moving into mobile contexts. However, screen size of mobile devices is limited and search engine result pages face a trade-off between offering informative snippets and optimal use of space. One factor clearly influencing this trade-off is snippet length. The purpose of this paper is to find out what snippet size to use in mobile web search.

Design/methodology/approach

For this purpose, an eye-tracking experiment was conducted showing participants search interfaces with snippets of one, three or five lines on a mobile device to analyze 17 dependent variables. In total, 31 participants took part in the study. Each of the participants solved informational and navigational tasks.

Findings

Results indicate a strong influence of page fold on scrolling behavior and attention distribution across search results. Regardless of query type, short snippets seem to provide too little information about the result, so that search performance and subjective measures are negatively affected. Long snippets of five lines lead to better performance than medium snippets for navigational queries, but to worse performance for informational queries.

Originality/value

Although space in mobile search is limited, this study shows that longer snippets improve usability and user experience. It further emphasizes that page fold plays a stronger role in mobile than in desktop search for attention distribution.

Details

Aslib Journal of Information Management, vol. 71 no. 3
Type: Research Article
ISSN: 2050-3806

Keywords

Access Restricted. View access options
Article
Publication date: 1 December 2000

M. Landoni, R. Wilson and F. Gibb

This paper presents the results of two studies into electronic book production. The Visual book study explored the importance of the visual component of the book metaphor for the…

1953

Abstract

This paper presents the results of two studies into electronic book production. The Visual book study explored the importance of the visual component of the book metaphor for the production of more effective electronic books, while the WEB book study took the findings of the Visual book and applied them to the production of books for publication on the World Wide Web (WWW). Both studies started from an assessment of which kinds of paper book are more suitable for translation into electronic form. Both also identified publications which are meant to be used for reference rather than those which are read sequentially, and usually in their entirety. This group includes scientific publications and textbooks which were both used as the target group for the Visual book and the WEB book experiments. In this paper we discuss the results of the two studies and how they could influence the design and production of more effective electronic books.

Details

The Electronic Library, vol. 18 no. 6
Type: Research Article
ISSN: 0264-0473

Keywords

Access Restricted. View access options
Article
Publication date: 11 June 2021

Wei Du, Qiang Yan, Wenping Zhang and Jian Ma

Patent trade recommendations necessitate recommendation interpretability in addition to recommendation accuracy because of patent transaction risks and the technological…

736

Abstract

Purpose

Patent trade recommendations necessitate recommendation interpretability in addition to recommendation accuracy because of patent transaction risks and the technological complexity of patents. This study designs an interpretable knowledge-aware patent recommendation model (IKPRM) for patent trading. IKPRM first creates a patent knowledge graph (PKG) for patent trade recommendations and then leverages paths in the PKG to achieve recommendation interpretability.

Design/methodology/approach

First, we construct a PKG to integrate online company behaviors and patent information using natural language processing techniques. Second, a bidirectional long short-term memory network (BiLSTM) is utilized with an attention mechanism to establish the connecting paths of a company — patent pair in PKG. Finally, the prediction score of a company — patent pair is calculated by assigning different weights to their connecting paths. The semantic relationships in connecting paths help explain why a candidate patent is recommended.

Findings

Experiments on a real dataset from a patent trading platform verify that IKPRM significantly outperforms baseline methods in terms of hit ratio and normalized discounted cumulative gain (nDCG). The analysis of an online user study verified the interpretability of our recommendations.

Originality/value

A meta-path-based recommendation can achieve certain explainability but suffers from low flexibility when reasoning on heterogeneous information. To bridge this gap, we propose the IKPRM to explain the full paths in the knowledge graph. IKPRM demonstrates good performance and transparency and is a solid foundation for integrating interpretable artificial intelligence into complex tasks such as intelligent recommendations.

Details

Internet Research, vol. 32 no. 2
Type: Research Article
ISSN: 1066-2243

Keywords

Access Restricted. View access options
Article
Publication date: 6 February 2009

Noorhidawati Abdullah and Forbes Gibb

The purpose of this paper is to present the third of three inter‐related experiments investigating the use and usability of e‐books in Higher Education based on experiments…

1377

Abstract

Purpose

The purpose of this paper is to present the third of three inter‐related experiments investigating the use and usability of e‐books in Higher Education based on experiments conducted at the University of Strathclyde. This study has looked in greater detail at user interactions with e‐books for reference purposes by focusing on searching and browsing tasks using three search tools: back‐of the‐book index (BoBI), table of contents (ToC) and full text search (FTS).

Design/methodology/approach

This study was carried out by subject‐specific users and using a between‐subjects approach. The target population was MSc and research students in the Department of Computer and Information Sciences, at the University of Strathclyde and involved a total of 45 responses.

Findings

The study found that a BoBI was more efficient compared to a ToC and FTS tool for finding information in an e‐book environment. A BoBI was found to perform the best for accurately finding relevant content in e‐books. The usability evaluation also found that a BoBI was more useful compared to a ToC for finding information in an e‐book environment.

Research limitations/implications

The study was focused only on the usability of e‐books, and in particular on retrieval performance, user satisfaction and preferences regarding BoBI, ToC and FTS, and not on other features such as the user interface. The e‐book usability evaluation was constrained in so far as the e‐books used were: non‐fiction; in the domain of information retrieval; e‐books that already had BoBIs with hyperlinks from the BoBI to the text; e‐books that had ToCs with hyperlinks; e‐books that had FTS tools; and e‐books that were available in PDF format.

Practical implications

The study is important in gaining a better understanding of the retrieval performance of three search tools (BoBI, ToC and FTS) for browsing for relevant, and searching for specific, information in e‐books. This will be of value for designing better e‐books and access systems.

Originality/value

The strengths and novelty of this study are the methodology that was used, the comprehensive inter‐comparison of tools, and the size of the population. The findings have supported empirically – through an assessment of the performances of BoBIs and ToCs – the need for an enhanced library catalogue system in order to improve users’ browsing and searching capabilities for relevant book content.

Details

Library Review, vol. 58 no. 1
Type: Research Article
ISSN: 0024-2535

Keywords

1 – 10 of 98
Per page
102050