Autor:

Moldovan, Andreea ; Bot, Radu Ioan ; Wanka, Gert

Współtwórca:

Beliczyński, Bartłomiej - red.

Tytuł:

Latent semantic indexing for patent documents

Podtytuł:

Intelligent Control and Signal Processing

Tytuł publikacji grupowej:

AMCS, Volume 15 (2005)

Temat i słowa kluczowe:

Latent Semantic Indexing (LSI) ; Singular Value Decomposition (SVD) ; Vector Space Model (VSM) ; patent classification

Abstract:

Since the huge database of patent documents is continuously increasing, the issue of classifying, updating and retrievingpatent documents turned into an acute necessity. Therefore, we investigate the efficiency of applying Latent SemanticIndexing, an automatic indexing method of information retrieval, to some classes of patent documents from the UnitedStates Patent Classification System. We present some experiments that provide the optimal number of dimensions for theLatent Semantic Space and we compare the performance of Latent Semantic Indexing (LSI) to the Vector Space Model(VSM) technique applied to real life text documents, namely, patent documents. However, we do not strongly recommendthe LSI as an improved alternative method to the VSM, since the results are not significantly better.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2005

Typ zasobu:

artykuł

Strony:

551-560

Źródło:

AMCS, Volume 15, Number 4 (2005) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego