Sentence examples for using a vector space from inspiring English sources

In this paper we adapt scalable statistical techniques to perform this summarization under a predictive framework using a vector space model of documents.

We propose and analyze a generalized self-healing key distribution using a vector space access structure in order to reach more flexible performance of the scheme.

In this paper, a content-based text mining technique is adopted to extract the textual content of a CAD document into a characteristic document (CD), which can be retrieved with similarity matching using a Vector Space Model (VSM), so that the automated and expedited retrievals of CAD documents from vast CAD databases become possible.

One common method for similarity measurement is to first assign a weight to each term in the document by using the number of times the term occurs, then invert the number of occurrences of the term in all documents ((tfidf_{t,d})) [2, 3], and finally calculate the similarity based on the weighting results using a vector space model [4].

Thus, GO-based similarity of gene pairs was calculated using a vector space model.

One of the simplest way how to represent the occurrence of terms (key words or key phrases) in any text document is to use a vector space model (VSM).

Baroni et al. (2010) suggests extracting a property list from a corpus which can be used as a vector space representation.

Let us assume we are using a Gaussian vector space kernel as defined in equation (5).

The conjugate gradient method is used to compute the optimizing value of a function defined on a vector space, using only first derivation information.

Lin et al. [21] transform the video sequence into a vector space using a Lie algebraic representation.

Instead, we are for the alias matching problem making use of a vector space-representation for the various aliases, where each feature corresponds to a single dimension in the vector space.