… of the basic combinatorial search problem: let \(q\) be a prime power and \(\mathrm{GF}(q)\)
the finite field of \(q\) elements. Let \(V\) denote an \(n\)-dimensional vector space over \(\…

… In this paper we presented a novel distributed Web service search engine based on the
Vector Space Model for information retrieval. We gave an overview of the underlying …

… between terms can be discovered in the vector space model. Such comparisons aid in the
refinement of searches based on the vector space model. The SVD allows such comparisons …

… The problem of searching the elements of a set that are close … space, instead of the more
restricted case of a vector space. … the intrinsic difficulty of the search problem. This includes a …

… We introduce a novel latent vector space model that … vector space models (LSI, LDA and
word2vec) and evaluate it as a feature in a learning to rank setting. Our latent vector space …

… In this study, the researcher explored the problems embedded in this process, attempted
to find solutions such as the way of choosing mutation probability and fitness function, and …

… vector space model. In Section 4, an overview of the steps involved in the proposed
generalization of the vector space … The basic premise in the vector space model is that the various …

… in a re-ranking scenario and, consequently, we compare NVSM only to latent vector
space models that can be queried using a nearest neighbor search. The following latent …

… of structures with a high anomaly can be performed using a vector space search. Vector
Space Search. We provide an efficient algorithm performing this search: given a set \(\mathcal {S…

… the problem of searching for vectors similar to a query vector in a large database. The typical
applications are the search … where documents are represented by feature vectors [1]. In this …