Congratulations to Dr Lee Chei Sian and Dr Alton Chua on their sucessful AcRF research grant applications!

• Investigating the Effective Use of Social Computing Applications: The Role of Individual Differences (PI: Lee Chei Sian) (see abstract below)
• Automated User-Based Question-Answering System (PI: Alton Chua) (see abstract below)

Investigating the Effective Use of Social Computing Applications: The Role of Individual Differences (AcRF research grant, Principle Investigator: Dr Lee Chei Sian)

Social computing has transformed the way people communicate, share and collaborate online. Undoubtedly, the accessibility and shared computing resources brought about by social computing applications are having a profound impact on individuals and organizations. Here, a fundamental issue is the relationship between the type of applications available and the individuals that employ them. While work in this area is nascent, early research has indicated that individual differences appear to play an important role in how and what social computing applications (e.g. blogs, wikis, social network services) are used to explore opportunities, or to manage problems or issues. The objective of the project is to expand our knowledge on the use of a variety of social computing applications and how these applications can be integrated to afford individuals the resources they need to support social interactions at work or at play. 

Automated User-Based Question-Answering System (AcRF research grant, Principle Investigator: Dr Alton Chua)

Unlike search engines, Question Answering (QA) systems provide concise answers to questions formulated in natural language. Automated QA systems accept users’ question and return sentences from Web pages deemed to contain relevant answers. On the other hand, user-based QA systems allow users to post questions and receive answers offered voluntarily by others.  In Automated QA systems, research gaps exist in the area of question-clustering and answer-selection. In user-based QA systems, current research efforts fail to address how the heavy dependence on other users’ participation can be alleviated. Moreover, scholarly inquiries into these two systems have yet to dovetail into a composite research stream where techniques gleaned from automated QA systems could be exploited for user-based QA systems.  For these reasons, this proposal seeks to develop a coalesced research perspective on QA systems.  Specifically, its aims are to:  (1) develop an efficacious question-clustering technique intended for managing user-generated content; (2) develop a theoretical model that selects and ranks answers; (3) design and develop a content-extraction system that harness content from Web 2.0 platforms;  and (4) implement and evaluate an automated user-based QA system which does not rely on the goodwill of users’ participation.