In this paper, we introduce the PARADISE search engine in TREC09 Web track. PARADISE is the abbreviation for Platform for Applying, Research and Developing Intelligent Search Engine, which is a search engine platform developed by SEWM group, Peking University. The system is designed to support both English and Chinese information retrieval. This system preprocessed and indexed the five hundred ...

We investigated the extent to which the human capacity for recognition helps to forecast political elections: We compared naïve recognition-based election forecasts computed from convenience samples of citizens’ recognition of party names to (i) standard polling forecasts computed from representative samples of citizens’ voting intentions, and to (ii) simple—and typically very accurate—wisdom-o...

We study an endogenous opinion (or, belief) dynamics model where we endogenize the social network that models the link (‘trust’) weights between agents. Our network adjustment mechanism is simple: an agent increases her weight for another agent if that agent has been close to truth (whence, our adjustment criterion is ‘past performance’). Moreover, we consider multiply biased agents that do not...

There are statements I wish to protest in the Focus article "Trouble in Paradise" by John F. Lauerman published in Environmental Health Perspectives [105:914-917 (1997)]. These statements appear to have been attributed to me, but I can assure you I would never have made them. First, there is the suggestion that I included atrazine among a list of agricultural chemicals used in pineapple cultiva...

The design of methods for performance evaluation is a major open research issue in the area of spoken language dialogue systems. This paper presents the PARADISE methodology for developing predictive models of spoken dialogue performance, and shows how to evaluate the predictive power and generalizability of such models. To illustrate the methodology, we develop a number of models for predictin...

This article presents the participation of the medGIFT group in ImageCLEFmed 2013. Since 2004, the group has participated in the medical image retrieval tasks of ImageCLEF each year. There are four types of tasks for ImageCLEFmed 2013: modality classification, image– based retrieval, case–based retrieval and a new task on compound figure separation. The medGIFT group participated in all four ta...