In this paper we address the problem of question recommendation from large archives of community question answering data by exploiting the users’ information needs. Our experimental results indicate that questions based on the same or similar information need can provide excellent question recommendation. We show that translation model can be effectively utilized to predict the information need...

This study examines reformulations of queries submitted to a search engine of a university Web site with a focus on (implicitly derived) user satisfaction and the performance of the underlying search engine. Using a search log of a university Web site we examined all reformulations submitted in a 10-week period and studied the relation between the popularity of the reformulation and the perform...

Entity recommendation, providing entity suggestions relevant to the query that a user is searching for, has become a key feature of today’s web search engine. Despite the fact that related entities are relevant to users’ search queries, sometimes users cannot easily understand the recommended entities without evidences. This paper proposes a statistical model consisting of four sub-models to ge...

The goal of a citation recommendation system is to suggest some references for a snippet in an article or a book, and this is very useful for both authors and the readers. The citation recommendation problem can be cast as an information retrieval problem, in which the query is the snippet from an article, and the relevant documents are the cited articles. In reality, the citation snippet and t...

Initially popularized by Amazon.com, recommendation technologies have become widespread over the past several years. However, the types of recommendations available to the users in these recommender systems are typically determined by the vendor and therefore are not flexible. In this paper we address this problem by presenting the recommendation query language REQUEST that allows users to cust...

In this paper I propose a method that, given a query submitted to a search engine, suggests a list of related queries. Query recommendation is a method to improve search results in web. This paper presents a method for mining search engine query logs to obtain fast query recommendation on a large scale. Search engines generally return long list of ranked pages, finding the important information...

Recently, growth of internet has been increased for information retrieval though it is difficult to extract the relevant information in less time. Search engine sometime fails to understand user search intend. Query recommendation can be used to help user to state exactly their information need. Search engine can return appropriate result to meet users’ information needs. There are various meth...

Initially popularized by Amazon.com, recommendation technologies have become widespread over the past several years, both in the industry and academia. The traditional two-dimensional approach to recommender systems, involving the dimensions of Users and Items, has been subsequently extended to the multidimensional approach supporting additional contextual dimensions and OLAP-type aggregation c...

Personalised recommender systems aim to help users retrieve relevant information from large collections, by automatically finding and suggesting products of likely interest based on observed evidence of the users’ preferences. These preferences are difficult to guess, and therefore recommender systems have a considerable variance in their success ratio in estimating the user’s tastes and intere...

In this article we propose an interactive Web-based movie recommendation system namely MISRec employing object recognition for movie thumbnails. The proposed system carries out object recognition on movie thumbnails or DVD cover-photos in a real-time manner, and recommends movies based on user’s historical preferences and the query intention. Unlike typical preference-based recommendation syste...