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This paper proposes a method of assisting movie summarization using plotinformation. A plot of a movie available at Wikipedia contains a majorstory of the movie. From such a plot of a movie, we extract severalimportant sentences as the content of summary. For summarizing movie, the key work is finding the best alignment between sentences of plot andshots which are segmented from a movie. There are...
The innovative brand “The internet of Me” is a recent research area that highlight the prevalence of personalization across the internet and focuses on the user habits and actions tracked from his interaction with the web content. This paradigm presents an efficient way to define the user experience, preferences useful in e-commerce, marketing, social and search purpose. In this paper we are interested...
With the ever expanding mobile device ecosystem, mobile users face a vast and constantly growing application pool. At the same time, in our daily life, waiting occurs regularly at different places such as shopping centers, where mobile applications become the de facto means to consume the time periods. In this paper, we propose a novel application recommendation system that utilizes human activity...
This paper describes a method for automatically ranking a dictionary of swear words based on their level of rudeness. The final ranking is generated by combining two baseline rankings: 1) using the normalized accumulated cosine similarity between the word embeddings of the swear word and the n-best list of closest neighborhoods, and 2) using a pseudo-relevance feedback and bootstrapping algorithm...
In recent years content aggregation Internet forums are used more and more by Internet users to locate and get a copy of digital culture goods, which makes them another main consumption place for digital culture goods besides BitTorrent websites. In this paper we give our recent study on a forum called Wawa city to show how these content aggregation Internet forums work, how users behave and what...
A good movie is like a good book. As a good book can serve entertaining and learning purposes, so does a movie. In addition to that, movies are in general more engaging and reach a wider audience. In this work, we present and evaluate a method that overcomes the challenge of generating recommendations among heterogeneous resources. In our case, we recommend movies in the context of a learning object...
We report on experiments that demonstrate the relevance of our AntiSocial Behavior (ASB) corpus as a machine learning resource to detect antisocial behavior from text. We first describe the corpus and then, by using the corpus for training machine learning algorithms, we build a set of binary classifiers. Experimental evaluations revealed that classifiers built based on the ASB corpus produce reliable...
A knowledge infusion process gives a system the linguistic and cultural knowledge—normally the prerogative of human beings—required to play a complex language game.
This paper applies the relatively new concept of the Long Tail to classroom environments thereby offering a new way of viewing student participation and engagement. We suggest that Web 2.0 technologies such as forums and wikis will appeal to the Long Tail of low-involvement students to increase their interactions within learning environments in the same way that Internet search and recommendation...
Semantic wikis constitute an increasingly popular class of systems for collaborative knowledge engineering. We developed Loki, a semantic wiki that uses a logic-based knowledge representation. It is compatible with semantic annotations mechanism as well as Semantic Web languages. We integrated the system with a rule engine called Heart that supports inference with production rules. Several modes for...
This paper proposes that Wikipedia can effectively be used in order to lessen the negative effects of data sparsity on the accuracy of recommendations produced by Recommender Systems, provided that domain resources available for recommendation can successfully be mapped to Wikipedia articles. Under the assumption that hyperlinks between Wikipedia articles convey latent semantic relationships between...
This paper presents a new method to find leading indicators of domestic book sales from conventional Blog information. Although Blog information is different from actual purchases, it will influence customer behaviors. They consider it would be useful for decision making of businesses and organizations. Main contributions of the paper are three fold: 1) As well as study on the US of an Internet bookstore,...
Recognizing the alternative ways people use to reference an entity, is important for many Web applications that query structured data. In such applications, there is often a mismatch between how content creators describe entities and how different users try to retrieve them. In this paper, we consider the problem of determining whether a candidate query approximately matches with an entity. We propose...
We explore several ways to estimate movie similarity from the free encyclopedia Wikipedia with the goal of improving our predictions for the Netflix Prize. Our system first uses the content and hyperlink structure of Wikipedia articles to identify similarities between movies. We then predict a user's unknown ratings by using these similarities in conjunction with the user's known ratings to initialize...
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