CIKM

As soon as natural disaster events happen, users are eager to know more about them. However, search engines currently provide a ten blue links interface for queries related to such events. Relevance of results for such queries can be significantly ...

Word vectors are distributed representations of word features. Continuous Bag-of-Words Model(CBOW) is a state-of-the-art model for learning word vectors, yet can be ameliorated for learning better word vectors because we find that CBOW is vulnerable to ...

JSON is a popular web data interchange format in Internet, especially for Social Network applications. To process these current JSON data sets using Semantic Web technologies, we should firstly convert them into well-defined semantic description ...

With the development of academic research, the number of scientific papers has risen sharply, there is an urgent need to assist researchers in locating the candidate cited papers they are looking for. Classical relation-based and text-based approaches ...

There is an increasing popularity of people posting their feelings on microblogging such as Twitter. Sentiment analysis on the tweets allows organizations to monitor public' feelings towards a product or brand. In this paper, we model sentiment analysis ...

Clustering is an important technique in organising and categorising web scale documents. The main challenges faced in clustering the billions of documents available on the web are the processing power required and the sheer size of the datasets ...

Several authors have developed relation extraction methods for automatically learning or refining taxonomies from large text corpora such as the Web. However, without appropriate post-processing, such taxonomies are often inconsistent (e.g. they contain ...

Bayesian network (BN) with latent variables (LVs) provides a concise and straightforward framework for representing and inferring uncertain knowledge with unobservable variables or with regard to missing data. To learn the BN with LVs consistently with ...

This paper addresses the problem of matching between highly heterogeneous structures. The problem is modeled as a classification task where training examples are used to learn the matching between structures. In our approach, training is performed using ...

Query auto-completion (QAC) is one of the most recognizable and widely used services of modern search engines. Its goal is to assist a user in the process of query formulation. Current QAC systems are mainly reactive. They respond to the present request ...

With governments and administrations releasing open linked data, and with the gradual rise of sensor deployments across the world, semantic queries on the combined sensor and linked data has become a need to provide several intelligent smart city ...

Recently, social networks have attracted considerable attention. The huge volume of information contained in them, as well as their dynamic nature, make the problem of searching social data challenging. In this work, we envision the design of a complete ...