Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
WordNet: a lexical database for English
Communications of the ACM
A syntactic approach for searching similarities within sentences
Proceedings of the eleventh international conference on Information and knowledge management
An Adapted Lesk Algorithm for Word Sense Disambiguation Using WordNet
CICLing '02 Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing
Sentence Similarity Based on Semantic Nets and Corpus Statistics
IEEE Transactions on Knowledge and Data Engineering
WordNet: similarity - measuring the relatedness of concepts
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Corpus-based and knowledge-based measures of text semantic similarity
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Text-to-text semantic similarity for automatic short answer grading
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Understanding the value of features for coreference resolution
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
LexRank: graph-based lexical centrality as salience in text summarization
Journal of Artificial Intelligence Research
The role of sentence structure in recognizing textual entailment
RTE '07 Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
A short text modeling method combining semantic and statistical information
Information Sciences: an International Journal
SyMSS: A syntax-based measure for short-text semantic similarity
Data & Knowledge Engineering
Open information extraction: the second generation
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
SemEval-2012 task 6: a pilot on semantic textual similarity
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
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In this paper, we describe the system architecture used in the Semantic Textual Similarity (STS) task 6 pilot challenge. The goal of this challenge is to accurately identify five levels of semantic similarity between two sentences: equivalent, mostly equivalent, roughly equivalent, not equivalent but sharing the same topic and no equivalence. Our participations were two systems. The first system (rule-based) combines both semantic and syntax features to arrive at the overall similarity. The proposed rules enable the system to adequately handle domain knowledge gaps that are inherent when working with knowledge resources. As such one of its main goals, the system suggests a set of domain-free rules to help the human annotator in scoring semantic equivalence of two sentences. The second system is our baseline in which we use the Cosine Similarity between the words in each sentence pair.