Vector Space Model based on Semantic Attributes of Words.
نویسندگان
چکیده
منابع مشابه
Pacific Association for Computational Linguistics VECTOR SPACE MODEL BASED ON SEMANTIC ATTRIBUTES OF WORDS
In order to reduce the dimension of VSM (Vector Space Model) for information retrieval and clustering, this paper proposes a new method, Semantic-VSM, which uses the Semantic Attribute System defined by ”A-Japanese-Lexicon” instead of literal words used in conventional VSM. The attribute system consists of a tree structure with 2,710 attributes, which includes 400 thousand literal words. Using ...
متن کاملmortality forecasting based on lee-carter model
over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent d...
15 صفحه اولELMDist: A Vector Space Model with Words and MusicBrainz Entities
Music consumption habits as well as the Music market have changed dramatically due to the increasing popularity of digital audio and streaming services. Today, users are closer than ever to a vast number of songs, albums, artists and bands. However, the challenge remains in how to make sense of all the data available in the Music domain, and how current state of the art in Natural Language Proc...
متن کاملA Generalized Vector Space Model for Text Retrieval Based on Semantic Relatedness
Generalized Vector Space Models (GVSM) extend the standard Vector Space Model (VSM) by embedding additional types of information, besides terms, in the representation of documents. An interesting type of information that can be used in such models is semantic information from word thesauri like WordNet. Previous attempts to construct GVSM reported contradicting results. The most challenging pro...
متن کاملA Systematic Study of Semantic Vector Space Model Parameters
We present a systematic study of parameters used in the construction of semantic vector space models. Evaluation is carried out on a variety of similarity tasks, including a compositionality dataset, using several source corpora. In addition to recommendations for optimal parameters, we present some novel findings, including a similarity metric that outperforms the alternatives on all tasks con...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Natural Language Processing
سال: 2003
ISSN: 1340-7619,2185-8314
DOI: 10.5715/jnlp.10.2_111