The increasing online content has influenced users’ buying behavior. It has triggered a paradigm shift in marketing strategies, as the consumer is no longer swayed by marketers, instead relying on user comments for a particular product or service. This paper focuses on extracting information from feedbacks like suggestions and recommendation by the users that is often present along with the sen...

The growing acceptance of consciousness as a legitimate field of enquiry and the availability of functional imaging has rekindled research interest in the use of hypnosis and suggestion to manipulate subjective experience and to gain insights into healthy and pathological cognitive functioning. Current research forms two strands. The first comprises studies exploring the cognitive and neural na...

Many query suggestion techniques have been proposed to better capture user intent and to improve search effectiveness. However, most of these methods make use of query logs which are not readily available to the research community. Anchor text, on the other hand, is widely available and has proven useful for many tasks. In this paper, we investigate the problem of query suggestion via random wa...

This paper describes our work on the Contextual Suggestion Track of the Twenty-Third Text REtrieval Conference (TREC 2014). The key to our approach is user interest modeling. By building explicit models of user interests and information needs, we are able to make suggestions relevant to the user. We extended our Reinforcement and Aging Modeling Algorithm (RAMA) to create user interest models us...

Query suggestion attracts great concern recently. It is crucial for capturing frequently asked questions in question-answering system and most popular topics in search engine. Besides these, is also used in advertising retrieval systems, e-commerce system for advertising push to get more profits. The paper gives a general review of query suggestion methods. On the whole, all the methods can be ...