Comparison of algorithms for patent documents clusterization

D. Kukolj, Z. Tekic, Lj Nikolic, Z. Panjkov, M. Pokric, M. Drazic, M. Vitas, D. Nemet

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

Ever increasing number of patents makes impossible to find and analyze relevant documents manually. Various software tools have been developed in the patent field. They could analyze individual patents as well as patent portfolios; retrieve patents and make basic statistics as well as visualize, map and landscape the same data. The essential function any tool should provide is patent clustering. There have been many different clustering approaches. In this paper we compare performances of k-means, the neural-gas, fuzzy c-means and ronn clustering technique when used on patent data set that was also clustered by the experts.

Original languageEnglish
Title of host publicationMIPRO 2012 - 35th International Convention on Information and Communication Technology, Electronics and Microelectronics - Proceedings
Pages995-997
Number of pages3
Publication statusPublished - 2012
Externally publishedYes
Event35th International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2012 - Opatija, Croatia
Duration: 21 May 201225 May 2012

Publication series

NameMIPRO 2012 - 35th International Convention on Information and Communication Technology, Electronics and Microelectronics - Proceedings

Conference

Conference35th International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2012
Country/TerritoryCroatia
CityOpatija
Period21/05/1225/05/12

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