A New Suffix Tree Similarity Measure and Labeling for Web Search Results Clustering

Kale, Archana; Bharambe, Ujwala; SashiKumar, M.

doi:10.1109/icetet.2009.13

Cited by 3 publications

(3 citation statements)

References 26 publications

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“…IV. SUFFIX TREE CLUSTERING ALGORITHM Suffix Tree Clustering [1,12] uses the concept of document clustering for clustering the documents. Document clustering is the process of organizing the documents into groups.…”

Section: Disadvantagesmentioning

confidence: 99%

“…And the algorithm uses these suffixes to identify the base clusters. [1,12,17,18] There are many document clustering algorithms for efficient search result. They produce the result according to the users query.…”

Section: Disadvantagesmentioning

confidence: 99%

“…Algorithm [1,12] The suffix tree clustering algorithm applies on the documents to fast and efficient searching. Suffix tree clustering produces the better result than the other clustering algorithm.…”

Section: Algorithm Steps For Suffix Tree Clusteringmentioning

confidence: 99%

See 2 more Smart Citations

An Analytical Assessment on Document Clustering

Pushplata¹,

Chatterjee²

2012

IJCNIS

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Clustering is related to data mining for information retrieval. Relevant information is retrieved quickly while doing the clustering of documents. It organizes the documents into groups; each group contains the documents of similar type content. Document clustering is an unsupervised approach of data mining. Different clustering algorithms are used for clustering the documents such as partitioned clustering (K-means Clustering) and Hierarchical Clustering (Agglomerative Hierarchical Clustering (AHC)). This paper presents analysis of Suffix Tree Clustering (STC) Algorithm and other clustering techniques (K-means, AHC) that are being done in literature survey. The paper also focuses on traditional Vector Space Model (VSM) for similarity measures, which is used for clustering the documents. This paper also focuses on the comparison of different clustering algorithms. STC algorithm improves the searching performance as compare to other clustering algorithms as the papers studied in literature survey. The paper presents STC algorithm applied on the search result documents, which is stored in the dataset. This paper articulates the key requirements for web document clustering and clusters would be created on the full text of the web documents. STC perform the clustering and make the clusters based on phrases shared between the documents. STC is faster clustering algorithm for document clustering.

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Section: Disadvantagesmentioning

confidence: 99%

Section: Disadvantagesmentioning

confidence: 99%