In this work, a benchmark to evaluate the retrieval performance of soundtrack recommendation systems is proposed. Such systems aim at finding songs that are played as background music for a given set of images. The proposed benchmark is based on preference judgments, where relevance is considered a continuous ordinal variable and judgments are collected for pairs of songs with respect to a quer...

Bayesian approaches to utility elicitation typically adopt (myopic) expected value of information (EVOI) as a natural criterion for selecting queries. However, EVOI-optimization is usually computationally prohibitive. In this paper, we examine EVOI optimization using choice queries, queries in which a user is ask to select her most preferred product from a set. We show that, under very general ...

This work reports on the applicability of the Broadway recommendation computation approach for implementing a query reenement (QR) service in the context of a distributed information retrieval and gathering system. The Broadway recommendation approach is based on the following hypothesis: recommend to one user items or actions that have satissed users that have behaved similarly to her/him. The...

Finding relevant research works from the large number of published articles has become a nontrivial problem. In this paper, we consider the problem of citation recommendation where the query is a set of seed papers. Collaborative filtering and PaperRank are classical approaches for this task. Previous work has shown PaperRank achieves better recommendation in experiments. However, the running t...

Search engine provide query recommendation which suggest user to choose any one query from their recommendation list according to their necessities. Such systems had been expected to have a good result, especially in E-commerce and E-learning environments. However, although they have been intensively explored in the Web Mining and Machine learning fields, and there have been some commercialized...

In this paper, we propose a distributed recipe recommendation mechanism that utilizes social information for adaptive recipe recommendation in a peer-to-peer (P2P) network. A recipe flavor model is first proposed for modeling recipes and validating recipe adaptations. Peers in the network group themselves into communities in which members share common preferences of recipe data. This is helpful...

The rapid growth of research in biology, and the increasing degree to which different subareas of biology are connected, make it difficult to monitor the published literature effectively. To address this problem, we develop a reading recommendation system that requires no other input from users except their reading or citation history. This frees the users from the problem of expressing their i...

The goal of people recommender system is to generate meaningful social suggestion to users. The abundant data are the key factor in fulfilling a recommendation task, but the cost of user data in a real-world system is high. In this paper, we propose a novel approach that integrates a global search result with a personalized people recommendation system. Our approach utilizes the user identity a...

Visual data exploration allows users to analyze datasets based on visualizations of interesting data characteristics, to possibly discover interesting information about the data that users are a priori unaware of. In this context, both recommendations of queries selecting the data to be visualized and recommendations of visualizations that highlight interesting data characteristics support user...