This thesis aims to address the current limitations in short texts clustering and provides a systematic framework that includes three novel methods to effectively measure similarity of two short texts, efficiently group short texts, and dynamically cluster short text streams
In the information age, short texts are being encountered at numerous instances and in large quantit...
Natural Language Processing has become a common tool to extract relevant information from unstructur...
In natural language processing, short-text semantic similarity (STSS) is a very prominent field. It ...
In this paper, we describe the algorithm of narrow-domain short texts clustering, which is based on ...
International audienceRecently there has been an increase in interest towards clustering short text ...
The recent increase in the widespread use of short messages, for example micro-blogs or SMS communic...
In this paper, we describe the algorithm of narrow-domain short texts clustering, which is based on ...
Clustering narrow domain short texts is considered to be a complex task because of the intrinsic fea...
13301甲第4317号博士(工学)金沢大学博士論文要旨Abstract 以下に掲載:Journal of Software Engineering and Applications 7(8) pp....
Very short texts, such as tweets and invoices, present challenges in classification. Such texts abou...
We consider a challenging clustering task: the clustering of muti-word terms without document co-occ...
AbstractText clustering is an important application of data mining. It is concerned with grouping si...
Conventional lexical-clustering algorithms treat text fragments as a mixed collection of words, with...
International audienceWe consider a challenging clustering task: the clustering of multi-word terms ...
Text clustering plays a key role in navigation and browsing process. For an efficient text clusterin...
In the information age, short texts are being encountered at numerous instances and in large quantit...
Natural Language Processing has become a common tool to extract relevant information from unstructur...
In natural language processing, short-text semantic similarity (STSS) is a very prominent field. It ...
In this paper, we describe the algorithm of narrow-domain short texts clustering, which is based on ...
International audienceRecently there has been an increase in interest towards clustering short text ...
The recent increase in the widespread use of short messages, for example micro-blogs or SMS communic...
In this paper, we describe the algorithm of narrow-domain short texts clustering, which is based on ...
Clustering narrow domain short texts is considered to be a complex task because of the intrinsic fea...
13301甲第4317号博士(工学)金沢大学博士論文要旨Abstract 以下に掲載:Journal of Software Engineering and Applications 7(8) pp....
Very short texts, such as tweets and invoices, present challenges in classification. Such texts abou...
We consider a challenging clustering task: the clustering of muti-word terms without document co-occ...
AbstractText clustering is an important application of data mining. It is concerned with grouping si...
Conventional lexical-clustering algorithms treat text fragments as a mixed collection of words, with...
International audienceWe consider a challenging clustering task: the clustering of multi-word terms ...
Text clustering plays a key role in navigation and browsing process. For an efficient text clusterin...
In the information age, short texts are being encountered at numerous instances and in large quantit...
Natural Language Processing has become a common tool to extract relevant information from unstructur...
In natural language processing, short-text semantic similarity (STSS) is a very prominent field. It ...