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Article

Xiu Susie Fang, Quan Z. Sheng, Xianzhi Wang, Anne H.H. Ngu and Yihong Zhang

This paper aims to propose a system for generating actionable knowledge from Big Data and use this system to construct a comprehensive knowledge base (KB), called GrandBase.

Abstract

Purpose

This paper aims to propose a system for generating actionable knowledge from Big Data and use this system to construct a comprehensive knowledge base (KB), called GrandBase.

Design/methodology/approach

In particular, this study extracts new predicates from four types of data sources, namely, Web texts, Document Object Model (DOM) trees, existing KBs and query stream to augment the ontology of the existing KB (i.e. Freebase). In addition, a graph-based approach to conduct better truth discovery for multi-valued predicates is also proposed.

Findings

Empirical studies demonstrate the effectiveness of the approaches presented in this study and the potential of GrandBase. The future research directions regarding GrandBase construction and extension has also been discussed.

Originality/value

To revolutionize our modern society by using the wisdom of Big Data, considerable KBs have been constructed to feed the massive knowledge-driven applications with Resource Description Framework triples. The important challenges for KB construction include extracting information from large-scale, possibly conflicting and different-structured data sources (i.e. the knowledge extraction problem) and reconciling the conflicts that reside in the sources (i.e. the truth discovery problem). Tremendous research efforts have been contributed on both problems. However, the existing KBs are far from being comprehensive and accurate: first, existing knowledge extraction systems retrieve data from limited types of Web sources; second, existing truth discovery approaches commonly assume each predicate has only one true value. In this paper, the focus is on the problem of generating actionable knowledge from Big Data. A system is proposed, which consists of two phases, namely, knowledge extraction and truth discovery, to construct a broader KB, called GrandBase.

Details

PSU Research Review, vol. 1 no. 2
Type: Research Article
ISSN: 2399-1747

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Article

Yilu Zhou and Yuan Xue

Strategic alliances among organizations are some of the central drivers of innovation and economic growth. However, the discovery of alliances has relied on pure manual…

Abstract

Purpose

Strategic alliances among organizations are some of the central drivers of innovation and economic growth. However, the discovery of alliances has relied on pure manual search and has limited scope. This paper proposes a text-mining framework, ACRank, that automatically extracts alliances from news articles. ACRank aims to provide human analysts with a higher coverage of strategic alliances compared to existing databases, yet maintain a reasonable extraction precision. It has the potential to discover alliances involving less well-known companies, a situation often neglected by commercial databases.

Design/methodology/approach

The proposed framework is a systematic process of alliance extraction and validation using natural language processing techniques and alliance domain knowledge. The process integrates news article search, entity extraction, and syntactic and semantic linguistic parsing techniques. In particular, Alliance Discovery Template (ADT) identifies a number of linguistic templates expanded from expert domain knowledge and extract potential alliances at sentence-level. Alliance Confidence Ranking (ACRank)further validates each unique alliance based on multiple features at document-level. The framework is designed to deal with extremely skewed, noisy data from news articles.

Findings

In evaluating the performance of ACRank on a gold standard data set of IBM alliances (2006–2008) showed that: Sentence-level ADT-based extraction achieved 78.1% recall and 44.7% precision and eliminated over 99% of the noise in news articles. ACRank further improved precision to 97% with the top20% of extracted alliance instances. Further comparison with Thomson Reuters SDC database showed that SDC covered less than 20% of total alliances, while ACRank covered 67%. When applying ACRank to Dow 30 company news articles, ACRank is estimated to achieve a recall between 0.48 and 0.95, and only 15% of the alliances appeared in SDC.

Originality/value

The research framework proposed in this paper indicates a promising direction of building a comprehensive alliance database using automatic approaches. It adds value to academic studies and business analyses that require in-depth knowledge of strategic alliances. It also encourages other innovative studies that use text mining and data analytics to study business relations.

Details

Information Technology & People, vol. 33 no. 5
Type: Research Article
ISSN: 0959-3845

Keywords

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Article

Mohamed Morsey, Jens Lehmann, Sören Auer, Claus Stadler and Sebastian Hellmann

DBpedia extracts structured information from Wikipedia, interlinks it with other knowledge bases and freely publishes the results on the web using Linked Data and SPARQL…

Abstract

Purpose

DBpedia extracts structured information from Wikipedia, interlinks it with other knowledge bases and freely publishes the results on the web using Linked Data and SPARQL. However, the DBpedia release process is heavyweight and releases are sometimes based on several months old data. DBpedia‐Live solves this problem by providing a live synchronization method based on the update stream of Wikipedia. This paper seeks to address these issues.

Design/methodology/approach

Wikipedia provides DBpedia with a continuous stream of updates, i.e. a stream of articles, which were recently updated. DBpedia‐Live processes that stream on the fly to obtain RDF data and stores the extracted data back to DBpedia. DBpedia‐Live publishes the newly added/deleted triples in files, in order to enable synchronization between the DBpedia endpoint and other DBpedia mirrors.

Findings

During the realization of DBpedia‐Live the authors learned that it is crucial to process Wikipedia updates in a priority queue. Recently‐updated Wikipedia articles should have the highest priority, over mapping‐changes and unmodified pages. An overall finding is that there are plenty of opportunities arising from the emerging Web of Data for librarians.

Practical implications

DBpedia had and has a great effect on the Web of Data and became a crystallization point for it. Many companies and researchers use DBpedia and its public services to improve their applications and research approaches. The DBpedia‐Live framework improves DBpedia further by timely synchronizing it with Wikipedia, which is relevant for many use cases requiring up‐to‐date information.

Originality/value

The new DBpedia‐Live framework adds new features to the old DBpedia‐Live framework, e.g. abstract extraction, ontology changes, and changesets publication.

Details

Program, vol. 46 no. 2
Type: Research Article
ISSN: 0033-0337

Keywords

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Article

Ahsan Mahmood, Hikmat Ullah Khan, Zahoor Ur Rehman, Khalid Iqbal and Ch. Muhmmad Shahzad Faisal

The purpose of this research study is to extract and identify named entities from Hadith literature. Named entity recognition (NER) refers to the identification of the…

Abstract

Purpose

The purpose of this research study is to extract and identify named entities from Hadith literature. Named entity recognition (NER) refers to the identification of the named entities in a computer readable text having an annotation of categorization tags for information extraction. NER is an active research area in information management and information retrieval systems. NER serves as a baseline for machines to understand the context of a given content and helps in knowledge extraction. Although NER is considered as a solved task in major languages such as English, in languages such as Urdu, NER is still a challenging task. Moreover, NER depends on the language and domain of study; thus, it is gaining the attention of researchers in different domains.

Design/methodology/approach

This paper proposes a knowledge extraction framework using finite-state transducers (FSTs) – KEFST – to extract the named entities. KEFST consists of five steps: content extraction, tokenization, part of speech tagging, multi-word detection and NER. An extensive empirical analysis using the data corpus of Urdu translation of Sahih Al-Bukhari, a widely known hadith book, reveals that the proposed method effectively recognizes the entities to obtain better results.

Findings

The significant performance in terms of f-measure, precision and recall validates that the proposed model outperforms the existing methods for NER in the relevant literature.

Originality/value

This research is novel in this regard that no previous work is proposed in the Urdu language to extract named entities using FSTs and no previous work is proposed for Urdu hadith data NER.

Details

The Electronic Library , vol. 37 no. 2
Type: Research Article
ISSN: 0264-0473

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Article

Mona Mohamed, Sharma Pillutla and Stella Tomasi

The purpose of this paper is to establish a new conceptual iterative framework for extracting knowledge from open government data (OGD). OGD is becoming a major source for…

Abstract

Purpose

The purpose of this paper is to establish a new conceptual iterative framework for extracting knowledge from open government data (OGD). OGD is becoming a major source for knowledge and innovation to generate economic value, if properly used. However, currently there are no standards or frameworks for applying knowledge continuum tactics, techniques and procedures (TTPs) to improve elicit knowledge extraction from OGD in a consistent manner.

Design/methodology/approach

This paper is based on a comprehensive review of literature on both OGD and knowledge management (KM) frameworks. It provides insights into the extraction of knowledge from OGD by using a vast array of phased KM TTPs into the OGD lifecycle phases.

Findings

The paper proposes a knowledge iterative value network (KIVN) as a new conceptual model that applies the principles of KM on OGD. KIVN operates through applying KM TTPs to transfer and transform discrete data into valuable knowledge.

Research limitations/implications

This model covers the most important knowledge elicitation steps; however, users who are interested in using KIVN phases may need to slightly customize it based on their environment and OGD policy and procedure.

Practical implications

After its validation, the model allows facilitating systemic manipulation of OGD for both data-consuming industries and data-producing governments to establish new business models and governance schemes to better make use of OGD.

Originality/value

This paper offers new perspectives on eliciting knowledge from OGD and discussing crucial, but overlooked area of the OGD arena, namely, knowledge extraction through KM principles.

Details

VINE Journal of Information and Knowledge Management Systems, vol. 50 no. 3
Type: Research Article
ISSN: 2059-5891

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Article

Ramana Rao and Ralph H. Sprague

This paper ‘looks” into one of the most novel knowledge management technology products that has been brought to the market in the recent years. The authors describe two…

Abstract

This paper ‘looks” into one of the most novel knowledge management technology products that has been brought to the market in the recent years. The authors describe two technologies, information visualization and knowledge extraction, for leveraging our natural abilities of vision, language and memory. They discuss a way for exploiting structure that is available in the information system in one case (traditionally called structured) and easily perceived by humans in the other (traditionally called unstructured). The two technologies focus on the two sides of this goal, respectively. They demonstrate the value of these technologies in supporting interaction with much larger amounts of information than was possible with previous graphical interfaces and in guiding access and use of the information and often for automating portions of the work.

Details

Journal of Knowledge Management, vol. 2 no. 2
Type: Research Article
ISSN: 1367-3270

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Article

Chyan Yang, Liang‐Chu Chen and Chun‐Yen Peng

This paper seeks to establish an extraction system for an information technology (IT) product specification named ITSIES which combines the natural language process (NLP…

Abstract

Purpose

This paper seeks to establish an extraction system for an information technology (IT) product specification named ITSIES which combines the natural language process (NLP) with the ontology concept and also to evaluate the system's effectiveness in advance.

Design/methodology/approach

The development of the system is based on a prototype design and performance validation. This study adopts four classes of IT specification (PC, Unix server, Monitor, and Printer) that follow IBM's and HP's product lines as the baseline information in order to construct the extraction system in GATE (General Architecture for Text Engineering) tools and to examine the IT product specification with other brands and patterns. Additionally indices are adopted such as precision, recall, and F‐measure as the matrices for evaluating system performance.

Findings

The performance shows that the average recall, precision, and F‐measure are all over 90 per cent, revealing that the JAPE (Java Annotation Patterns Engine) grammar rules in the IT domain are reasonably good and generally in line with expectations.

Originality/value

The paper proposes an integrative framework to examine IT product specification information and demonstrates that the system is effective for IT application.

Details

The Electronic Library, vol. 24 no. 6
Type: Research Article
ISSN: 0264-0473

Keywords

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Article

Toshihiro Ioi, Masakazu Ono, Kota Ishii and Kazuhiko Kato

The purpose of this paper is to propose a method for the transfer of knowledge and skills in project management (PM) based on techniques in knowledge management (KM).

Abstract

Purpose

The purpose of this paper is to propose a method for the transfer of knowledge and skills in project management (PM) based on techniques in knowledge management (KM).

Design/methodology/approach

The literature contains studies on methods to extract experiential knowledge in PM, but few studies exist that focus on methods to convert extracted knowledge into practical knowledge and transfer it to learners. This research proposes a model of PM skills transfer management, which consists of a PM knowledge extraction phase, PM knowledge recognition phase, practical knowledge transfer phase, and practical knowledge evaluation phase, and examines the model's effectiveness.

Findings

Through multi‐agent simulation (MAS), expert communities for knowledge extraction can be vitalized. A PM skills transfer management maturity model (PMST3M) was proposed that is capable of evaluating PM skills transfer management.

Research limitations/implications

The present work could have considered KSM in‐depth with a view to adding value to the virtualization of community of PM experts.

Originality/value

The paper presents a detailed critique of a knowledge‐management‐based process of transferring PM skills.

Details

Campus-Wide Information Systems, vol. 29 no. 4
Type: Research Article
ISSN: 1065-0741

Keywords

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Article

Auhood Alfaries, David Bell and Mark Lycett

The purpose of the research is to speed up the process of semantic web services by transformation of current Web services into semantic web services. This can be achieved…

Abstract

Purpose

The purpose of the research is to speed up the process of semantic web services by transformation of current Web services into semantic web services. This can be achieved by applying ontology learning techniques to automatically extract domain ontologies.

Design/methodology/approach

The work here presents a Service Ontology Learning Framework (SOLF), the core aspect of which extracts Structured Interpretation Patterns (SIP). These patterns are used to automate the acquisition (from production domain specific Web Services) of ontological concepts and the relations between those concepts.

Findings

A Semantic Web of accessible and re‐usable software services is able to support the increasingly dynamic and time‐limited development process. This is premised on the efficient and effective creation of supporting domain ontology.

Research limitations/implications

Though WSDL documents provide important application level service description, they alone are not sufficient for OL however, as: they typically provide technical descriptions only; and in many cases, Web services use XSD files to provide data type definitions. The need to include (and combine) other Web service resources in the OL process is therefore an important one.

Practical implications

Web service domain ontologies are the general means by which semantics are added to Web services; typically used as a common domain model and referenced by annotated or externally described Web artefacts (e.g. Web services). The development and deployment of Semantic Web services by enterprises and the wider business community has the potential to radically improve planned and ad‐hoc service re‐use. The reality is slower however, in good part because the development of an appropriate ontology is an expensive, error prone and labor intensive task. The proposed SOLF framework is aimed to overcome this problem by contributing a framework and a tool that can be used to build web service domain ontologies automatically.

Originality/value

The output of the SOLF process is an automatically generated OWL domain ontology, a basis from which a future Semantic Web Services can be delivered using existing Web services. It can be seen that the ontology created moves beyond basic taxonomy – extracting and relating concepts at a number of levels. More importantly, the approach provides integrated knowledge (represented by the individual WSDL documents) from a number of domain experts across a group of banks.

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Article

Yazhong Deng

The purpose of this study was to establish a massive online open course (MOOC)-based map of higher education knowledge and apply it to university libraries. It hoped to…

Abstract

Purpose

The purpose of this study was to establish a massive online open course (MOOC)-based map of higher education knowledge and apply it to university libraries. It hoped to provide more targeted and personalized learning services for every learner.

Design/methodology/approach

In this study, MOOC and university library information services were outlined, the development status of MOOC at home and abroad and the development of university library information services were introduced, and the necessity and significance of MOOC in developing information services in university libraries were analyzed. What is more, the knowledge map of university libraries was explored. The four modules include the construction of data sets, the identification of related entities from plain text, the extraction of entity relationships and the practical application of knowledge maps. For the logical relationship of the course, a combination of knowledge base and machine learning was adopted. In the knowledge map application module, the knowledge map was visualized. Aiming at the generation of personalized learning scheme, a prior data set was constructed by means of the knowledge base. The original problem was considered as a multi-classification problem. K-nearest neighbor classifier divided all courses into four academic years to obtain all courses. According to the course stage, the personalized learning scheme of some majors in higher education was obtained.

Findings

The experiment showed that it was feasible to apply the higher education knowledge map based on MOOC to university libraries. In addition, it was effective to divide the course into four stages by classifier. In this way, the specific professional training program can be obtained, the information service of the university library can be improved, and the accuracy and richness of the entire learning program can be increased.

Research limitations/implications

Due to the limitations of conditions, time and other aspects, there were not many opportunities to visit the field library, which led to limited level and imperfect research. There were many proper nouns and professional terms in foreign references, but my English translation ability was limited. The relevant investigation on foreign studies may not be detailed and comprehensive enough, and the analysis and induction of influencing factors of university library information service may not be rigorous and concise enough.

Practical implications

As the base of university information dissemination, the university library is the source of knowledge. At the same time, it is also the temple of students’ independent learning and the media of mainstream culture and improving its own information service level is also in line with the trend of The Times. Under this background, this research studied the influence of MOOC on university library information service and focused on the challenges and opportunities faced by university library information service in the MOOC environment, so as to continuously improve its cultural serviceability and better serve teachers and students.

Originality/value

Since the birth of MOOC, they have exerted great influence and enlightenment on universities and relevant educational institutions within a few years. European and American universities take an active part in the construction of the MOOC platform and explore how to make better use of the library to build MOOC resources in practice. It is also a hot topic for university libraries to participate in the construction of MOOC information resources. Therefore, the study of this topic has both theoretical and practical significance.

Details

The Electronic Library, vol. 37 no. 5
Type: Research Article
ISSN: 0264-0473

Keywords

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