Description: Text clustering algorithm is based on the similarity of automatic clustering techniques, automatically a large number of non-classified categories of documents, the contents of the documents fall into a similar category, and automatically generate the features for this kind of keywords. For automatic generation of hot topics of public opinion, major news event tracking, information visualization analysis and many other applications.
Ling Jiu Lingjoin (www.lingjoin.com) found that based on the core features of technology, a breakthrough of traditional clustering method of space consumption, processing time is long bottlenecks not only the clustering speed and high accuracy, memory consumption is small, is particularly suitable for ultra-large-scale corpus clustering and short text corpus clustering.
Ling-Jiu document clustering component of the main features are:
1, fast: the size of the network can handle the massive text data, the average hourly processing at least 50 mil
File list (Check if you may need any files):
LJClusterDemo\Dict.pdat
.............\Dict.wordlist
.............\LJCluster.dll
.............\LJClusterDemo.exe
.............\LJCluster说明.txt
.............\stop.ung
LJClusterDemo
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