In this paper we present our technique for finding semantically similar clusters within web documents obtained from a set of queries retrieved from the Google search engine. This ...
Personalized Web search has emerged as one of the hottest topics for both the Web industry and academic researchers. However, the majority of studies on personalized search focuse...
Jae-wook Ahn, Peter Brusilovsky, Daqing He, Jonath...
We formulate and study search algorithms that consider a user’s prior interactions with a wide variety of content to personalize that user’s current Web search. Rather than re...
Search engines present fix-length passages from documents ranked by relevance against the query. In this paper, we present and compare novel, language-model based methods for extr...
Postcorrection of OCR-results for text documents is usually based on electronic dictionaries. When scanning texts from a specific thematic area, conventional dictionaries often m...
Christian M. Strohmaier, Christoph Ringlstetter, K...