Revision as of 17:48, March 10, 2013 by Emijrp (Text replace - "<h2> Datasets </h2> There is no datasets for this keyword. <h2> Tools </h2> There is no tools for this keyword. <br clear="all" /> <h2> Publications </h2> There is no publications with this keyword." to "")
| Literature review|
(Alternative names for this keyword)
|Related keyword(s)||Systematic literature review|
|Export and share|
|BibTeX, CSV, RDF, JSON|
|Browse properties · List of keywords|
Literature review is included as keyword or extra keyword in 0 datasets, 0 tools and 7 publications.
There is no datasets for this keyword.
There is no tools for this keyword.
|Title||Author(s)||Published in||Language||DateThis property is a special property in this wiki.||Abstract||R||C|
|Social software in new product development - State of research and future research directions||Rohmann S.
|20th Americas Conference on Information Systems, AMCIS 2014||English||2014||Product development becomes increasingly collaborative and knowledge-intensive in today's industry. To gain competitive advantage an effective usage of information systems in new product development (NPD) is needed. Social software applications indicate further potential for usage in NPD, the so called "Product Development 2.0", which is poorly understood in research so far. The purpose of this article is to point out the current state of research in this area by means of a literature review, after which research gaps and future research directions are identified. The results indicate that social software applications are suitable to support tasks in all phases of the NPD process, but influencing factors and effects of the identified social software usage in NPD are poorly understood so far.||0||0|
|Ontology-based identification of research gaps and immature research areas||Beckers K.
|Lecture Notes in Computer Science||English||2012||Researchers often have to understand new knowledge areas, and identify research gaps and immature areas in them. They have to understand and link numerous publications to achieve this goal. This is difficult, because natural language has to be analyzed in the publications, and implicit relations between them have to be discovered. We propose to utilize the structuring possibilities of ontologies to make the relations between publications, knowledge objects (e.g., methods, tools, notations), and knowledge areas explicit. Furthermore, we use Kitchenham's work on structured literature reviews and apply it to the ontology. We formalize relations between objects in the ontology using Codd's relational algebra to support different kinds of literature research. These formal expressions are implemented as ontology queries. Thus, we implement an immature research area analysis and research gap identification mechanism. The ontology and its relations are implemented based on the Semantic MediaWiki+ platform.||0||0|
|Using Wikipedia and conceptual graph structures to generate questions for academic writing support||Liu M.
|IEEE Transactions on Learning Technologies||English||2012||In this paper, we present a novel approach for semiautomatic question generation to support academic writing. Our system first extracts key phrases from students' literature review papers. Each key phrase is matched with a Wikipedia article and classified into one of five abstract concept categories: Research Field, Technology, System, Term, and Other. Using the content of the matched Wikipedia article, the system then constructs a conceptual graph structure representation for each key phrase and the questions are then generated based the structure. To evaluate the quality of the computer generated questions, we conducted a version of the Bystander Turing test, which involved 20 research students who had written literature reviews for an IT methods course. The pedagogical values of generated questions were evaluated using a semiautomated process. The results indicate that the students had difficulty distinguishing between computer-generated and supervisor-generated questions. Computer-generated questions were also rated as being as pedagogically useful as supervisor-generated questions, and more useful than generic questions. The findings also suggest that the computer-generated questions were more useful for the first-year students than for second or third-year students.||0||0|
|Using information extraction to generate trigger questions for academic writing support||Liu M.
|Lecture Notes in Computer Science||English||2012||Automated question generation approaches have been proposed to support reading comprehension. However, these approaches are not suitable for supporting writing activities. We present a novel approach to generate different forms of trigger questions (directive and facilitative) aimed at supporting deep learning. Useful semantic information from Wikipedia articles is extracted and linked to the key phrases in a students' literature review, particularly focusing on extracting information containing 3 types of relations (Kind of, Similar-to and Different-to) by using syntactic pattern matching rules. We collected literature reviews from 23 Engineering research students, and evaluated the quality of 306 computer generated questions and 115 generic questions. Facilitative questions are more useful when it comes to deep learning about the topic, while directive questions are clearer and useful for improving the composition.||0||0|
|Social information systems: Review, framework, and research agenda||Schlagwein D.
|International Conference on Information Systems 2011, ICIS 2011||English||2011||In this research-in-progress, we review the literature on an emerging new type of information systems: social information systems. Social information systems are information systems based on social technologies and open collaboration. The paper provides categories defining social information systems and a framework for existing and future research in this field of study.||0||0|
|Protocol for a systematic literature review of research on the Wikipedia||Chitu Okoli
|International Conference on Management of Emergent Digital EcoSystems||English||2009||Context: Wikipedia has become one of the ten-most visited sites on the Web, and the world's leading source of Web reference information. Its rapid success has attracted over 1,000 scholarly studies that treat Wikipedia as a major topic or data source. Objectives: This article presents a protocol for conducting a systematic mapping (a broad-based literature review) of research on Wikipedia. It identifies what research has been conducted; what research questions have been asked, which have been answered; and what theories and methodologies have been employed to study Wikipedia. Methods: This protocol follows the rigorous methodology of evidence-based software engineering to conduct a systematic mapping study. Results and conclusions: This protocol reports a study in progress.||0||1|
|Library 2.0: A review of the literature||Boxen J.L.||Reference Librarian||English||2008||In recent years the professional literature has seen an increase in articles written about Library 2.0 implementation in academic reference departments. These articles have focused on the integration and introduction of services such as blogs, wikis, social networking Websites, RSS, and podcasting. This article reviews the content of this literature to see which articles demonstrate a qualitative or quantitative benefit to the libraries where they are used.||0||0|
- See also: List of literature reviews.