Latent Semantic Indexing for patent documents
International Journal of Applied Mathematics and Computer Science, Tome 15 (2005) no. 4, p. 551.

Voir la notice de l'article dans European Digital Mathematics Library

Since the huge database of patent documents is continuously increasing, the issue of classifying, updating and retrieving patent documents turned into an acute necessity. Therefore, we investigate the efficiency of applying Latent Semantic Indexing, an automatic indexing method of information retrieval, to some classes of patent documents from the United States Patent Classification System. We present some experiments that provide the optimal number of dimensions for the Latent 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 recommend the LSI as an improved alternative method to the VSM, since the results are not significantly better.
Classification : 68P20
Mots-clés : patent classification, Latent Semantic Indexing (LSI), Vector Space Model (VSM), Singular Value Decomposition (SVD), vector space model 
@article{IJAMCS_2005__15_4_207766,
     author = {Andreea Moldovan and Radu Bo\c{t} and Gert Wanka},
     title = {Latent {Semantic} {Indexing} for patent documents},
     journal = {International Journal of Applied Mathematics and Computer Science},
     pages = {551},
     publisher = {mathdoc},
     volume = {15},
     number = {4},
     year = {2005},
     zbl = {1107.68414},
     language = {en},
     url = {https://geodesic-test.mathdoc.fr/item/IJAMCS_2005__15_4_207766/}
}
TY  - JOUR
AU  - Andreea Moldovan
AU  - Radu Boţ
AU  - Gert Wanka
TI  - Latent Semantic Indexing for patent documents
JO  - International Journal of Applied Mathematics and Computer Science
PY  - 2005
SP  - 551
VL  - 15
IS  - 4
PB  - mathdoc
UR  - https://geodesic-test.mathdoc.fr/item/IJAMCS_2005__15_4_207766/
LA  - en
ID  - IJAMCS_2005__15_4_207766
ER  - 
%0 Journal Article
%A Andreea Moldovan
%A Radu Boţ
%A Gert Wanka
%T Latent Semantic Indexing for patent documents
%J International Journal of Applied Mathematics and Computer Science
%D 2005
%P 551
%V 15
%N 4
%I mathdoc
%U https://geodesic-test.mathdoc.fr/item/IJAMCS_2005__15_4_207766/
%G en
%F IJAMCS_2005__15_4_207766
Andreea Moldovan; Radu Boţ; Gert Wanka. Latent Semantic Indexing for patent documents. International Journal of Applied Mathematics and Computer Science, Tome 15 (2005) no. 4, p. 551. https://geodesic-test.mathdoc.fr/item/IJAMCS_2005__15_4_207766/