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The ability to identify, process, and comprehend the essential elements of information associated with a given operational environment can be used to reason about how the actors within the environment can best respond. This is often referred to as "situation assessment," the end state of which is "situation awareness," which can be simply defined as "knowing what is going...
It is presented an approach aimed at analyzing the homepage of a Facebook user or group in order to automatically detect who has discussed what and how it has been discussed. All public posts shared by an user are retrieved by an ad hoc built crawler. Information such as a text messages, comments, likes, is extracted for each post. Each post is classified as belonging to a set of predefined categories...
We present a simple approach to handle recursive SPARQL queries, that is, nested queries that may contain references to the query itself. This powerful feature is obtained by implementing a custom SPARQL function that takes a SPARQL query as a parameter and executes it over a specified endpoint. The behaviour is similar to the SPARQL 1.1 SERVICE clause, with a few fundamental differences: (1) the...
There is a growing need to make sense of all the raw data available on the Internet, hence, the purpose of this study is to explore the capabilities of data mining algorithms applied to social networks. We propose a system to mine public Twitter data for information relevant to obesity and health as an initial case study. This paper details the findings of our project and critiques the use of social...
In this paper, we represent a dynamic context-dependent weighting method for vector space model. A meaning is relatively decided by a context dynamically. A vector space model, including latent semantic indexing (LSI), etc. relatively measures correlations of each target thing that represents in each vector. However, the vectors of each target thing in almost method of the vector space models are...
In recent years, we have witnessed a deluge of multimedia data such as texts, images, and videos. However, the research of managing and retrieving these data efficiently is still in the development stage. The conventional tag-based searching approaches suffer from noisy or incomplete tag issues. As a result, the content-based multimedia data management framework has become increasingly popular. In...
Innovative analysis methods applied to data extracted by off-the-shelf peripherals can provide useful results in activity recognition without requiring large computational resources. In this paper a framework is proposed for automated posture and gesture recognition, exploiting depth data provided by a commercial tracking device. The detection problem is handled as a semantic-based resource discovery...
Big data processing is one of the hot scientific issues in the current social development. MapReduce is an important foundation for big data processing. In this paper, we propose a semantic++ MapReduce. This study includes four parts. (1) Semantic++ extraction and management for big data. We will do research about the automatically extracting, labeling and management methods for big data's semantic++...
In this paper we propose a simple and completely automatic methodology for analyzing sentiment of users in Twitter. Firstly, we built a Twitter corpus by grouping tweets expressing positive and negative polarity through a completely automatic procedure by using only emoticons in tweets. Then, we have built a simple sentiment classifier where an actual stream of tweets from Twitter is processed and...
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