Comparison of algorithms for patent documents clusterization

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

Результат исследований: Глава в книге, отчете, сборнике статейМатериалы для конференциирецензирование

5 Цитирования (Scopus)

Аннотация

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.

Язык оригиналаАнглийский
Название основной публикацииMIPRO 2012 - 35th International Convention on Information and Communication Technology, Electronics and Microelectronics - Proceedings
Страницы995-997
Число страниц3
СостояниеОпубликовано - 2012
Опубликовано для внешнего пользованияДа
Событие35th International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2012 - Opatija, Хорватия
Продолжительность: 21 мая 201225 мая 2012

Серия публикаций

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

Конференция

Конференция35th International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2012
Страна/TерриторияХорватия
ГородOpatija
Период21/05/1225/05/12

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