This master thesis deals with the implementation of a search engine using Latent Semantic Indexing (LSI) called BoSSE. Four different search types were implemented which allow a search for documents or terms similar to a given term, query or document. These search types are evaluated and the importance of term weighting, exclusion of non content words and the right selection of k for the reduction of dimension are discussed. Furthermore, an introduction to Latent Semantic Indexing (LSI) and an explanation of the Singular Value Decomposition (SVD) is given
Document Clustering is an issue of measuring similarity between documents and grouping similar docum...
Latent Semantic Analysis (LSA) is a technique that analyzes relationships between documents and its ...
The task of information retrieval is to extract relevant documents for a certain query from the coll...
Our capabilities for collecting and storing data of all kinds are greater then ever. On the other si...
Keyword matching information retrieval systems areplagued with problems of noise in the document col...
The aim of this thesis is to examine how thesauri constructed with latent semantic indexing LSI are ...
Latent semantic indexing (LSI) can be used in patent searching to overcome drawbacks of Boolean sear...
With the electronic storage of documents comes the possibility of building search engines that can ...
A new method for automatic indexing and retrieval is described. The approach is to take advantage of...
The primary purpose of an information retrieval system is to retrieve all the relevant documents, wh...
Latent semantic analysis (LSA) is a technique that analyzes relationships between documents and its ...
In this paper we present a theoretical model for understanding the performance of Latent Semantic In...
It is a challenge task to discover major topics from text, which provide a better understanding of t...
[[abstract]]Latent Semantic Indexing (LSI) is a retrieval technique that employs Singular Value Deco...
A new method for automatic indexing and retrieval is described. The approach is to take advantage of...
Document Clustering is an issue of measuring similarity between documents and grouping similar docum...
Latent Semantic Analysis (LSA) is a technique that analyzes relationships between documents and its ...
The task of information retrieval is to extract relevant documents for a certain query from the coll...
Our capabilities for collecting and storing data of all kinds are greater then ever. On the other si...
Keyword matching information retrieval systems areplagued with problems of noise in the document col...
The aim of this thesis is to examine how thesauri constructed with latent semantic indexing LSI are ...
Latent semantic indexing (LSI) can be used in patent searching to overcome drawbacks of Boolean sear...
With the electronic storage of documents comes the possibility of building search engines that can ...
A new method for automatic indexing and retrieval is described. The approach is to take advantage of...
The primary purpose of an information retrieval system is to retrieve all the relevant documents, wh...
Latent semantic analysis (LSA) is a technique that analyzes relationships between documents and its ...
In this paper we present a theoretical model for understanding the performance of Latent Semantic In...
It is a challenge task to discover major topics from text, which provide a better understanding of t...
[[abstract]]Latent Semantic Indexing (LSI) is a retrieval technique that employs Singular Value Deco...
A new method for automatic indexing and retrieval is described. The approach is to take advantage of...
Document Clustering is an issue of measuring similarity between documents and grouping similar docum...
Latent Semantic Analysis (LSA) is a technique that analyzes relationships between documents and its ...
The task of information retrieval is to extract relevant documents for a certain query from the coll...