@article {310,
	title = {Playing games with information: Investigating perceptions of a mobile content sharing game},
	journal = {Journal of Digital Information Management},
	volume = {10},
	year = {2012},
	note = {Export Date: 10 July 2014},
	month = {2012},
	pages = {10 - 19},
	abstract = {We introduce Indagator (Latin for explorer), an application which incorporates multiplayer, pervasive gaming elements into mobile content sharing. Indagator allows users to annotate real world locations with multimedia content, and concurrently, provides opportunities for play through engaging interactive game elements. A study of Indagator was conducted to obtain usability feedback, and to examine the impact of the usability of its content sharing and gaming features on participants{\textquoteright} intention to use it. Participants used the software to complete a set of tasks and subsequently completed a questionnaire and attended an interview, both of which were to elicit their opinions on the usability of the system. Participants felt that the features in Indagator were able to support the objectives of content sharing and gaming, and that idea of gaming could be a motivator for content sharing. In terms of intention to use, usability of Indagator{\textquoteright}s gaming features emerged as significant predictors.},
	keywords = {Mobile Content Sharing Game, Social Computing, Usability, User Evaluation},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84863281265\&partnerID=40\&md5=41c91a3b7957ec0b637c641bf9ba9a6e},
	author = {Goh, D.H.-L. and Lee, C.S. and Chua, A.Y.K.}
}
@article {166,
	title = {Design and development of a Query Graph Visualization system},
	journal = {Journal of Digital Information Management},
	volume = {7},
	year = {2009},
	note = {Export Date: 10 July 2014},
	month = {2009},
	pages = {21 - 29},
	abstract = {Collaborative querying is a technique that harnesses the collective search experiences of users to assist in query formulation. We present the Query Graph Visualizer (QGV), a visual collaborative querying system that recommends related queries to a user{\textquoteright}s submitted query through a network visualization scheme. Users are able to explore the query network and select queries for execution on an information retrieval (IR) system. the QGV is not meant to be a replacement for IR systems but as a value-added module to help users search more effectively. Consequently, the QGV is not an IR system but works in tandem with existing IR systems. the design of the QGV is discussed, focusing on its architecture, the interaction between the QGV{\textquoteright}s main components and the implementation of the user interface. An evaluation of the QGV was also conducted to assess the performance of the system against to a conventional search engine. Results indicate that the evaluators who used the QGV completed their tasks much faster compared to those using a search engine alone. A usability evaluation also showed that the system complied with standard user interface heuristics.},
	keywords = {Collaborative querying, Information retrieval, Query Graph Visualize, Query network},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-70350660828\&partnerID=40\&md5=33ccaf28cf0dad32e0b47d01f84a8707},
	author = {Goh, D.H.-L. and Lee, C.S. and Chua, A.Y.K. and Luyt, B.}
}
