Recommender systems apply statistical and knowledge discovery techniques to the problem of making recommendations during live user interaction. This paper describes a novel approach of building recommender systems for the Web with the aid of usergenerated content. Recently certain communities of Internet users have engaged in creating high quality peer reviewed content for the Web. In our appro...

To Find user’s frequent interest navigation patterns, we combine the information of web content and web server log, mine the web data to build a hidden markov model. In our approach, we build a hidden markov model according to page’s content and web service log firstly, and then we present a new incremental discovery algorithm Hmm_R to discover the interest navigation patterns. ...

Background. Physical education learning in the era of the COVID-19 pandemic has a remarkable impact on students’ creativity. Objectives. This study aims to determine the effect of applying the inquiry and discovery models in online physical education learning to develop high school students’ creativity. Methods. The multiple treatment and control with the pre and post-test procedure were used...

Theories about entrepreneurial discovery are important to entrepreneurship. However, the dominant conceptual foundation underlying such theories hinders their development. It assumes that opportunities form based on either deliberate search or serendipitous discovery. I examine this unidimensional logic and identify a gap in its informative content. Then, I reframe it into orthogonal dimensions...

This paper discusses an document discovery tool based on conceptual clustering by formal concept analysis. The program allows users to navigate email using a visual lattice metaphor rather than a tree. It implements a virtual le structure over email where les and entire directories can appear in multiple positions. The content and shape of the lattice formed by the conceptual ontology can assis...