Agglomerative hierarchical Clustering technique for partitioning patent dataset

Mining right patents from database have always been interesting and the most difficult task for analysis purposes. The choice of right data mining tool and algorithm is requisite for reducing the search space, thus enabling extraction of meaningful and useful information for technology forecasting. With clustering approach, this can be easily achieved. This paper discusses about Clustering technique called Agglomerative hierarchical clustering using Tanagra tool. It groups patents with similar characteristics into one cluster based on between sum of square (BSS ratio) and Gap parameters.