The main goal of this research is to improve Information Retrieval Systems by enabling them to generate search outcomes that are relevant and customized to each specific user. Our ...
It is crucial for a web crawler to distinguish between ephemeral and persistent content. Ephemeral content (e.g., quote of the day) is usually not worth crawling, because by the t...
A common limitation of many retrieval models, including the recently proposed axiomatic approaches, is that retrieval scores are solely based on exact (i.e., syntactic) matching o...
This work presents a study to bridge topic modeling and personalized search. A probabilistic topic model is used to extract topics from user search history. These topics can be se...
As with any application of machine learning, web search ranking requires labeled data. The labels usually come in the form of relevance assessments made by editors. Click logs can...