International audienceThe Cluster Hypothesis is the fundamental assumption of using clustering in Information Retrieval. It states that similar documents tend to be relevant to the same query. Past research works extensively test this hypothesis using agglomerative hierarchical clustering (AHC) methods. However, their conclusions are not consistent concerning retrieval effectiveness for a given clustering method. The main limit of these works is the scalability issue of AHC. In this paper, we extend our previous work to a new test of the cluster hypothesis by applying a scalable similarity-based AHC framework. Principally, the input pairwise cosine similarity matrix is sparsified by given threshold values to reduce memory usage and running ...
As a major type of unsupervised machine learning method, clustering has been widely applied in vario...
As a major type of unsupervised machine learning method, clustering has been widely applied in vario...
This paper is accepted as a long paper with an oral presentation by the IEEE international conferenc...
International audienceLance-Williams formula is a framework that unifies seven schemes of agglomerat...
The response to a query against the web or an enterprise’s electronic data can overwhelm the user si...
The response to a query against the web or an enterprise’s electronic data can overwhelm the user si...
The response to a query against the web or an enterprise’s electronic data can overwhelm the user si...
In this work, the agglomerative hierarchical clustering and K-means clustering algorithms are implem...
International audienceLance-Williams formula is a framework that unifies seven schemes of agglomerat...
A new means of evaluating the cluster hypothesis is introduced and the results of such an evaluatio...
This paper is accepted as a long paper with an oral presentation by the IEEE international conferenc...
Searching hierarchically clustered document collections can be effective, but creating the cluster ...
This paper is accepted as a long paper with an oral presentation by the IEEE international conferenc...
By allowing judgments based on a small number of exemplar documents to be applied to a larger number...
As a major type of unsupervised machine learning method, clustering has been widely applied in vario...
As a major type of unsupervised machine learning method, clustering has been widely applied in vario...
As a major type of unsupervised machine learning method, clustering has been widely applied in vario...
This paper is accepted as a long paper with an oral presentation by the IEEE international conferenc...
International audienceLance-Williams formula is a framework that unifies seven schemes of agglomerat...
The response to a query against the web or an enterprise’s electronic data can overwhelm the user si...
The response to a query against the web or an enterprise’s electronic data can overwhelm the user si...
The response to a query against the web or an enterprise’s electronic data can overwhelm the user si...
In this work, the agglomerative hierarchical clustering and K-means clustering algorithms are implem...
International audienceLance-Williams formula is a framework that unifies seven schemes of agglomerat...
A new means of evaluating the cluster hypothesis is introduced and the results of such an evaluatio...
This paper is accepted as a long paper with an oral presentation by the IEEE international conferenc...
Searching hierarchically clustered document collections can be effective, but creating the cluster ...
This paper is accepted as a long paper with an oral presentation by the IEEE international conferenc...
By allowing judgments based on a small number of exemplar documents to be applied to a larger number...
As a major type of unsupervised machine learning method, clustering has been widely applied in vario...
As a major type of unsupervised machine learning method, clustering has been widely applied in vario...
As a major type of unsupervised machine learning method, clustering has been widely applied in vario...
This paper is accepted as a long paper with an oral presentation by the IEEE international conferenc...