Titlebook: Web Information Systems Engineering -- WISE 2013; 14th International C Xuemin Lin,Yannis Manolopoulos,Guangyan Huang Conference proceedings

forebear

iPLUG: Personalized List Recommendation in Twitterrmation in tweets. The feature of . allows users to organize their followees into multiple subsets for selectively digesting tweets. However, this feature has not received wide reception because users are reluctant to invest initial efforts in manually creating lists. To address the challenge of boo

cultivated

The Irreducible Spine(s) of Undirected Networksits “spine”. The chordless cycles which comprise this irreducible core effectively characterize the connectivity structure of the network as a whole. In particular, it is shown that the center of the network, whether defined by distance or betweenness centrality, is effectively contained in this spi

occurrence

The Irreducible Spine(s) of Undirected Networksits “spine”. The chordless cycles which comprise this irreducible core effectively characterize the connectivity structure of the network as a whole. In particular, it is shown that the center of the network, whether defined by distance or betweenness centrality, is effectively contained in this spi

saphenous-vein

一再遛

,: Efficient Monitoring of Social Network Activitiesia–content examination has received limited attention. Such content examination involving multiple . gains significance as a way to either help us verify unconfirmed-thus-far evidence or expand our understanding about occurring events. Driven by the emerging requirement that future applications shal

Limerick

A Multiple Feature Integration Model to Infer Occupation from Social Media Recordsrecorded. Social media provides us an unprecedented way to collect and analyze billions of users’ information. Proper user attribute identification or profile inference becomes more and more attractive and feasible. However, the flourishing social records also pose great challenge in effective featu

exquisite

A Multiple Feature Integration Model to Infer Occupation from Social Media Recordsrecorded. Social media provides us an unprecedented way to collect and analyze billions of users’ information. Proper user attribute identification or profile inference becomes more and more attractive and feasible. However, the flourishing social records also pose great challenge in effective featu

索賠

Recommending Interesting Landmarks Based on Geo-tags from Photo Sharing Sitesa question, i.e., when we want to go sightseeing in a large city such as Beijing, where should we go? To achieve our goal, first, we present a data field clustering method (.). By using ., we can cluster a large-scale geo-tagged web photo collection into groups (or landmarks) by location. And then,

凹處

COST