In this work we present a novel item recommendation approach that aims at improving Collaborative Filtering (CF) in social tagging systems using the information about tags and time. Our algorithm follows a two-step approach, where in the first step a potentially interesting candidate item-set is found using user-based CF and in the second step this candidate item-set is ranked using item-based ...

In this work we present a novel item recommendation approach that aims at improving Collaborative Filtering (CF) in social tagging systems using the information about tags and time. Our algorithm follows a two-step approach, where in the first step a potentially interesting candidate item-set is found using user-based CF and in the second step this candidate item-set is ranked using item-based ...

This paper introduces a system designed for automatically generating personalized annotation tags to label Twitter user’s interests and concerns. We applied TFIDF ranking and TextRank to extract keywords from Twitter messages to tag the user. The user tagging precision we obtained is comparable to the precision of keyword extraction fromweb pages for content-targeted advertising.

1. Which category describes this manuscript? _X_Practice/Application/Case Study/Experience Report ___Research/Technology ___Survey/Tutorial/How-To B. Content 1. Please explain how this manuscript advances this field of research and/or contributes something new to the literature. The authors of the paper has found the use-generated tags sometimes are too meaningless to be used by current retriev...

In this paper, we describe our participation in the INEX 2014 Social Book Search(SBS) Track Suggestion Task. We investigate the contribution of user-generated data and construct a social book search system based on several important techniques. We perform re-ranking on Galago searching results on enriched XML index by 11 different strategies and combine the results with learning to rank. We fin...

In this paper we propose a dialogue act annotation system allowing ranking of communicative functions of utterances in terms of their subjective importance. It is argued that multidimensional dialogue act annotation schemes, while allowing more than one tag per utterance, implicitly treat all functions as equally important. Consequently, they fail to capture the fact that in a given context som...

In this paper, we describe our method and results for the MediaEval 2013 Retrieving Diverse Social Images Task. To accomplish the task objective, we adopt VisualRank [5] and Ranking with Sink Points [2], which are common methods to select representative and diverse photos. To obtain an affinity matrix for both ranking methods, we used only the officially-provided features including visual featu...

In this work we present a novel item recommendation approach that aims at improving Collaborative Filtering (CF) in social tagging systems using the information about tags and time. Our algorithm follows a two-step approach, where in the first step a potentially interesting candidate item-set is found using user-based CF and in the second step this candidate item-set is ranked using item-based ...

Social content systems contain enormous collections of unstructured user-generated content, annotated by the collaborative effort of regular Internet users. Tag-clouds have become popular interfaces that allow users to query the database by clicking relevant terms. However, these single click queries are often not expressive enough to effectively retrieve the desired content. Using both rating ...

Can we use the temporal evolution of annotations in Web images to improve tasks such as annotation, indexing and retrieval? This important question is the main motivation for this work. Typically visual content, text and metadata, are used to improve these tasks. A characteristic that has received less attention, so far, is the temporal aspect of social media production and tagging. The main co...