Alessandro Panunzi

Plagiarism Detection through Multilevel Text Comparison

The paper presents the implementation of a tool for plagiarism detection developed within the AXMEDIS project. The algorithm leverages the plagiarist behaviour, which is modeled as a combination of 3 basical actions: insertion, deletion, substitution. We recognize that this behaviour may occur at various level of the document structure: the plagiarist may insert, delete or substitute a word, period or a paragraph. The procedure consists in two main steps: document structure extraction and plagiarism function calculation. We propose a recursive plagiarism evaluation function to be evaluated at each level of the document structure which is based on the Levenshtein edit distance. We also propose a method that will eliminate unnecessary chunks comparison, avoiding similarity calculation of chunks which do not share enough 4-grams. We describe the similarity algorithm and discuss some implementation issues and future work

Keyword extraction in open-domain multilingual textual resources

The paper presents three methods for keyword extraction in open-domain multilingual textual resources, which will be implemented within the AXMEDIS framework. The procedures exploit, in an integrated architecture, statistic analysis and linguistic resources/tools, allowing document indexing and retrieval through high-level descriptors.

Measuring the Italian-English lexical gap for action verbs and its impact on translation

This paper describes a method to measure the lexical gap of action verbs in Italian and English by using the IMAGACT ontology of action. The fine-grained categorization of action concepts of the data source allowed to have wide overview of the relation between concepts in the two languages. The calculated lexical gap for both English and Italian is about 30% of the action concepts, much higher than previous results. Beyond this general numbers a deeper analysis has been performed in order to evaluate the impact that lexical gaps can have on translation. In particular a distinction has been made between the cases in which the presence of a lexical gap affects translation correctness and completeness at a semantic level. The results highlight a high percentage of concepts that can be considered hard to translate (about 18% from English to Italian and 20% from Italian to English) and confirms that action verbs are a critical lexical class for translation tasks.