A reliable mechanism for scoring the reputation of sellers is crucial for the development of a successful environment for customerto-customer e-commerce. Unfortunately, most C2C environments utilize simple feedback-based reputation systems, that not only do not offer sufficient protection from fraud, but tend to overestimate the reputation of sellers by introducing a strong bias toward maximizi...

The explosive growth of information on the World Wide Web demands eeective intelligent search and ltering methods. Consequently, techniques have been developed that extract conceptual information from documents to build domain models automatically. The model we build is a taxonomy of conceptual terms that is used in a search assistant to help the user navigate to the right set of required docum...

Acquiring novel speech categories is necessary in spoken language learning. The dual-learning systems (DLS) approach posits that two competitive systems underlie the category learning process: an explicit hypothesis-testing system, and an implicit procedural system. DLS assumes that the explicit system dominates early and control is passed to the implicit system when optimal. Evidence from our ...

Recommendation, collaboration and other tasks play important role on the adaptive web. For such tasks, user feedback is needed. Explicit feedback interrupts user and obtaining quality explicit feedback is problematic. On the other hand, users provide implicit feedback uninterrupted without knowing that they are rating. Traditional implicit feedback on the web – tracking of mouse and keyboard in...

Personalized ranking with implicit feedback (e.g. purchases, views, check-ins) is an important paradigm in recommender systems. Such feedback sometimes comes with textual information (e.g. reviews, comments, tips), which could be a useful signal to reveal item properties, identify users’ tastes and interpret their behavior. Although incorporating such information is common in explicit feedback ...