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Users tend to ask and answer questions in community question answering (CQA) services to seek information and share knowledge. A corollary is that myriad of questions and answers appear in CQA service. Accordingly, volumes of studies have been taken to explore the answer quality so as to provide a preliminary screening for better answers. However, to our(More)
In this paper, we investigate the novel problem of automatic question identification in the microblog environment. It contains two steps: detecting tweets that contain questions (we call them "interrogative tweets") and extracting the tweets which really seek information or ask for help (so called "qweets") from interrogative tweets. To detect interrogative(More)
Community Question Answering (CQA) service provides a platform for increasing number of users to ask and answer for their own needs but unanswered questions still exist within a fixed period. To address this, the paper aims to route questions to the right answerers who have a top rank in accordance of their previous answering performance. In order to rank(More)
With the rapid growth of the Internet, more and more people interact with their friends in online social networks like Facebook<sup>1</sup>. Current online social networks have designed some strategies to protect users' privacy, but they are not stringent enough. Some public information of profile or relationship can be utilized to infer users' private(More)
This paper investigates a ground-breaking incorporation of question category to Question Routing (QR) in Community Question Answering (CQA) services. The incorporation of question category was designed to estimate answerer expertise for routing questions to potential answerers. Two category-sensitive Language Models (LMs) were developed with large-scale(More)
This paper presents an initial attempt at the use of crowd-sourcing for collection of user judgments on spoken dialog systems (SDSs). This is implemented on Amazon Mechanical Turk (MTurk), where a Requester can design a human intelligence task (HIT) to be performed by a large number of Workers efficiently and cost-effectively. We describe a design(More)
Development of spoken dialog systems (SDSs) can be facilitated by better evaluation methods. Previous methods seldom consider the efficiency of the system, which is important to users. We study the problem of evaluating SDSs and propose a new framework by generalizing states from utterances of dialogs to build finite state machine (FSM). These states can be(More)
Developing accurate models to automatically predict user satisfaction about the overall quality of a Spoken Dialog System (SDS) is highly desirable for SDS evaluation. In the original PARADISE framework, a linear regression model is trained using measures drawn from rated dialogs as predic-tors with user satisfaction as the target. In this paper, we extend(More)
Community Question Answering (CQA) attracts increasing volume of research on question retrieval, high quality content discovery and experts finding. However, few studies are focused on community per se of CQA services and also provide an in-depth analysis of them. This paper aims to enrich our knowledge on two of these CQA services, namely Yahoo! Answers(More)
Community question answering services (CQA), which provides a platform for people with diverse backgrounds to share information and knowledge, has become an increasingly popular research topic recently as made popular by sites such as Yahoo! Answers<sup>1</sup>, answerbag<sup>2</sup>, zhidao<sup>3</sup>, etc. Question retrieval (QR) in CQA can automatically(More)