Christian Sánchez-Sánchez

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This paper describes the participation of the Language and Reasoning Group of UAM at RepLab 2014 Author Profiling evaluation lab. This task involves author categorization and author ranking subtasks. Our method for author categorization uses a supervised approach based on the idea that we can use the information on Twitter's user profile, then by means of(More)
In this article we deal with the Topic Detection and Priority Detection subtasks from RepLab 2013, trying clustering and classification methods as well as term selection techniques in order to know its performance in two sub collections of tweets: single and extended (single tweet plus derived tweets). Our tests show good performance in spite of we used(More)
In this paper we describe the participation of the Language and Reasoning group from UAM-C in the context of the Cross Language SOurce COde re-use competition (CL-SOCO 2015). We proposed a representation of source code pairs by using five high level features; namely: i) lexical feature, ii) stylistic feature, iii) comments feature, iv) programmer's text(More)
In this work, an interaction model between artificial life agents (creatures) is proposed, which allows studying emergent social behavior of agents. This model describes the environment of artificial life and autonomous creatures in terms of goal-states, rules of behavior based on agents' goals and actions, initial knowledge and the use of communication(More)
This paper describes the system developed by the Language and Reasoning Group of UAM for the Relevance Feedback track of INEX 2012. The presented system focuses on the problem of ranking documents in accordance to their relevance. It is mainly based on the following hypotheses: (i) current IR machines are able to retrieve relevant documents for most of(More)
Source code plagiarism can be identified by analyzing several and diverse views of a pair of source code. In this paper we present three representations from lexical and structural views of a given source code. We attempt to show that different representations provide diverse information that can be useful to identify plagiarism. In particular, we present(More)
Source code plagiarism can be identified by analyzing similarities of several and diverse aspects of a pair of source code. In this paper we present three types of similarity features that account for three aspects of source code documents, particularly: i) lexical, ii) structural, and iii) stylistics. From the lexical view, we used a character 3-gram model(More)
Nowadays, social networks have become an ideal tool for sharing information in real time. Different type of users use social media to comment about their activities, opinions, personal views, etc. The information poured in this media has become of particular interest to online reputation analysts, for instance, to identify relevant tendencies. 133 Research(More)