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In many practical recommender systems, it is found difficult to obtain explicit feedback from users about the preference for a specific item, such as music, book, movie, etc. Most researches up to this point has focused on tracking various sources of implicit feedback from user behavior including purchase history, browsing patterns, and watching habits, in order to model user preference. In this paper,...
Current blog systems rank `A-list' bloggers, but they are not necessarily influential. To differentiate influential bloggers from popular bloggers, we present important groundwork for identifying influential bloggers by weighting readers based on homophily and vulnerability with bloggers. We develop the Quantifying Influence Model (QIM), which attempts to measure the influence score of bloggers. QIM...
To extract and structure knowledge from unstructured tag sets is a challenge for the tagging system. Although several methods have shown the ability to assign structures to the tags, their limitation still remains. Accordingly, this study investigates a method to build the place hierarchy of geo-referenced tags. In particular, the method is based on analyzing geometric patterns of footprints, derived...
In social news services, selecting valuable and credible news content is one of the most important issues. In traditional journalism, a small number of people called editors selected news that they considered worthwhile. Recently, several services have utilized reader voting to find news that is popular or credible but most of them are prone to abuse. In this paper, we present a collaborative news...
With the change to Web 2.0 Internet environment and the popularization of blogs, people write various writings freely on the Internet such as daily events, movie reviews, news, etc. Here, we can find writings on personal experiences from the past or on past popular culture. This paper analyzed collective memory through the blogosphere. We define blog posts that qualify as containing collective memory,...
These days VLSC (very large-scale conversation) is a particular type of online conversation, that is large scale, public, text-based, many-to-many and persistent. The nature of VLSC allows the accumulation of thousands of conversation in a fraction of time, and it often grows out of userspsila readable capacity. Therefore, extracting dominant public opinion on VLSC is usually impossible without causing...
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