Word classification based on combined measures of distributional and semantic similarity
نویسندگان
چکیده
The paper addresses the problem of automatic enrichment of a thesaurus by classifying new words into its classes. The proposed classification method makes use of both the distributional data about a new word and the strength of the semantic relatedness of its target class to other likely candidate classes.
منابع مشابه
Measuring Semantic Distance using Distributional Profiles of Concepts
Automatic measures of semantic distance can be classified into two kinds: (1) those, such as WordNet, that rely on the structure of manually created lexical resources and (2) those that rely only on co-occurrence statistics from large corpora. Each kind has inherent strengths and limitations. Here we present a hybrid approach that combines corpus statistics with the structure of a Roget-like th...
متن کاملOn the use of distributional models of semantic space to investigate human cognition
Huettig et al. (2006) demonstrated that corpus-based measures of word semantics predict language-mediated eyemovements in the visual world. These data, in conjunction with the evidence from other tasks, is strong evidence for the psychological validity of corpusbased semantic similarity measures. But can corpus-based distributional models be more than just good measures of semantic similarity? ...
متن کاملA Supervised Learning Approach to Automatic Synonym Identification Based on Distributional Features
Distributional similarity has been widely used to capture the semantic relatedness of words in many NLP tasks. However, various parameters such as similarity measures must be handtuned to make it work effectively. Instead, we propose a novel approach to synonym identification based on supervised learning and distributional features, which correspond to the commonality of individual context type...
متن کاملUNIBA: Combining Distributional Semantic Models and Word Sense Disambiguation for Textual Similarity
This paper describes the UNIBA team participation in the Cross-Level Semantic Similarity task at SemEval 2014. We propose to combine the output of different semantic similarity measures which exploit Word Sense Disambiguation and Distributional Semantic Models, among other lexical features. The integration of similarity measures is performed by means of two supervised methods based on Gaussian ...
متن کاملCogALex-V Shared Task: LexNET - Integrated Path-based and Distributional Method for the Identification of Semantic Relations
We present a submission to the CogALex 2016 shared task on the corpus-based identification of semantic relations, using LexNET (Shwartz and Dagan, 2016), an integrated path-based and distributional method for semantic relation classification. The reported results in the shared task bring this submission to the third place on subtask 1 (word relatedness), and the first place on subtask 2 (semant...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2003