2,197 research outputs found
ENHANCING LITERATURE REVIEW METHODS - TOWARDS MORE EFFICIENT LITERATURE RESEARCH WITH LATENT SEMANTIC INDEXING
Nowadays, the facilitated access to increasing amounts of information and scientific resources means that more and more effort is required to conduct comprehensive literature reviews. Literature search, as a fundamental, complex, and time-consuming step in every literature research process, is part of many established scientific methods. However, it is still predominantly supported by search techniqus based on conventional term-matching methods. We address the lack of semantic approaches in this context by proposing an enhancement of established literature review methods. For this purpose, we followed design science research (DSR) principles in order to develop artifacts and implement a prototype of our Tool for Semantic Indexing and Similarity Quries (TSISQ) based on the core concepts of latent semantic indexing (LSI). Its applicability is demonstrated and evaluated in a case study. Results indicate that the presented approach can help save valuable time in finding basic literature in a desired research field or increasing the comprehensiveness of a review by efficiently identifying sources that otherwise would not have been taken into account. The target audience for our findings includes researchers who need to efficiently gain an overview of a specific research field, deepen their knowledge or refine the theoretical foundations of their research
Towards the new generation of web knowledge
Purpose - As the web evolves its purpose and nature of its use are changing. The purpose of the paper is to investigate whether the web can provide for the competing stakeholders, who are similarly evolving and who increasingly see it as a significant part of their business.
Design/methodology/approach - The paper adopts an exploratory and reviewing approach to the emerging trends and patterns emanating from the web's changing use and explores the underpinning technologies and tools that facilitate this use and access. It examines the future and potential of web-based knowledge management (KM) and reviews the emerging web trends, tools, and enabling technologies that will provide the infrastructure of the next generation web.
Findings - The research carried out provides an independent framework for the capturing, accessing and distributing of web knowledge. This framework retains the semantic mark-up, a feature that we deem indispensable for the future of KM, employing web ontologies to structure organisational knowledge and semantic text processing for the extraction of knowledge from web sites.
Practical implications - As a result it was possible to identify the implications of integrating the two aspects of web-based KM, namely the business-organisational-users' perspective and that of the enabling web technologies.
Originality/value - The proposed framework accommodates the collaborative tools and services offered by Web 2.0, acknowledging the fact that knowledge-based systems are shared, dynamic, evolving resources, whose underlying knowledge model requires careful management due to its constant changing
Nomenclature and Contemporary Affirmation of the Unsupervised Learning in Text and Document Mining
Document clustering is primarily a method applied for an uncomplicated, document search, analysis and review of content or is a process of automatic classification of documents of similar type categorized to relevant clusters, in a clustering hierarchy. In this paper a review of the related work in the field of document clustering from the simple techniques of word and phrase to the present complex techniques of statistical analysis, machine learning etc are illustrated with their implications for future research work
CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap
After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in
multimedia search engines, we have identified and analyzed gaps within European research effort during our second year.
In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio-
economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown
of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on
requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the
community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our
Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as
National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core
technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research
challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal
challenges
Enterprise Search in the European Union: A Techno-economic Analysis
This Report contributes to the work being carried out by IPTS on the potential of Search, discussing, in particular, the prospects of Enterprise search as well as the main challenges and opportunities. It is part of CHORUS+, an initiative supported by the Directorate General Information Society and Media. Information about CHORUS+ is available at http://avmediasearch.euJRC.J.3-Information Societ
Decision Support Capabilities of Enterprise Content Management Systems: An Empirical Investigation
Enterprise content management (ECM) systems help organizations cope with the increasing complexity and volume of data and information. Despite the growing popularity of ECM, published literature indicates that organizations primarily use ECM for operational benefits, while the strategic decision making capabilities are rarely considered. Thus, the most significant rewards of ECM implementation may be largely forgone. This study investigates the potential of ECM technology for decision support. A research model is proposed and validated via an empirical investigation. The results show that ECM positively influences problem identification and definition, decision making speed and analysis, decision quality, and decision makers’ satisfaction
Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure
Big data research has attracted great attention in science, technology,
industry and society. It is developing with the evolving scientific paradigm,
the fourth industrial revolution, and the transformational innovation of
technologies. However, its nature and fundamental challenge have not been
recognized, and its own methodology has not been formed. This paper explores
and answers the following questions: What is big data? What are the basic
methods for representing, managing and analyzing big data? What is the
relationship between big data and knowledge? Can we find a mapping from big
data into knowledge space? What kind of infrastructure is required to support
not only big data management and analysis but also knowledge discovery, sharing
and management? What is the relationship between big data and science paradigm?
What is the nature and fundamental challenge of big data computing? A
multi-dimensional perspective is presented toward a methodology of big data
computing.Comment: 59 page
Recommended from our members
Improving Discovery of and Access to Digital Repository Contents Using Semantic Web Standards: Columbia University’s Academic Commons
This article describes the progress made towards developing Academic Commons (AC), Columbia University’s digital repository, as an interoperable repository through the use of RDF and non-RDF Semantic Web technologies. Approaches taken include the implementation of microdata to add semantic markup to HTML content; a collaboration with Oregon State University’s (OSU) digital repository, ScholarsArchive@OSU (SA@OSU), to implement an application that indexes RDF data from OSU for use in AC; as well as an exploration of the recently released MODS RDF
Semantic technologies: from niche to the mainstream of Web 3? A comprehensive framework for web Information modelling and semantic annotation
Context: Web information technologies developed and applied in the last decade
have considerably changed the way web applications operate and have
revolutionised information management and knowledge discovery. Social
technologies, user-generated classification schemes and formal semantics have a
far-reaching sphere of influence. They promote collective intelligence, support
interoperability, enhance sustainability and instigate innovation.
Contribution: The research carried out and consequent publications follow the
various paradigms of semantic technologies, assess each approach, evaluate its
efficiency, identify the challenges involved and propose a comprehensive framework for web information modelling and semantic annotation, which is the thesis’ original contribution to knowledge. The proposed framework assists web information
modelling, facilitates semantic annotation and information retrieval, enables system interoperability and enhances information quality.
Implications: Semantic technologies coupled with social media and end-user
involvement can instigate innovative influence with wide organisational implications that can benefit a considerable range of industries. The scalable and sustainable business models of social computing and the collective intelligence of organisational social media can be resourcefully paired with internal research and knowledge from interoperable information repositories, back-end databases and legacy systems.
Semantified information assets can free human resources so that they can be used to better serve business development, support innovation and increase productivity
- …