Efficient Web Mining for Traversal Path Patterns

Chen, Zhixiang; Fowler, Richard H.; Fu, Ada Wai-Chee; Wang, Chunyue

doi:10.4018/9781591404149.ch015

Cited by 33 publications

(65 citation statements)

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“…Chen et al proposed a method to derive the longest access sequence and/or tree patterns among URLs (Chen, Park, & Yu, 1998). The method proposed by Liquiere and Sallantin completely searches homomorphically equivalent subgraphs (Liquiere & Sallantin, 1998).…”

Section: Discussion and Related Workmentioning

confidence: 99%

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2003

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Abstract. Basket Analysis, which is a standard method for data mining, derives frequent itemsets from database. However, its mining ability is limited to transaction data consisting of items. In reality, there are many applications where data are described in a more structural way, e.g. chemical compounds and Web browsing history. There are a few approaches that can discover characteristic patterns from graph-structured data in the field of machine learning. However, almost all of them are not suitable for such applications that require a complete search for all frequent subgraph patterns in the data. In this paper, we propose a novel principle and its algorithm that derive the characteristic patterns which frequently appear in graph-structured data. Our algorithm can derive all frequent induced subgraphs from both directed and undirected graph structured data having loops (including self-loops) with labeled or unlabeled nodes and links. Its performance is evaluated through the applications to Web browsing pattern analysis and chemical carcinogenesis analysis.

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Section: Discussion and Related Workmentioning

confidence: 99%

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2003

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“…One of its popular application is market basket analysis, which refers to the discovery of set of items that are frequently purchased by the customers. Frequent itemset mining [1] may discover the large amount of frequent but low revenue itemsets and lose the information on the valuable itemsets having low selling frequencies. These problems are caused by the following.…”

Section: Existing Systemmentioning

confidence: 99%

“…Each association rule has support (how common the precondition is in the dataset), confidence (how often the precondition leads to the consequence in the dataset). To mine the frequent itemsets the system addresses the use of Apriori algorithm.Apriori algorithm [1] is used for large transactional databases and it is very influential algorithm over other algorithms as other algorithms are derived from this algorithm. Apriori is a Bottom-up generation of Frequent item set combinations.…”

Section: Introductionmentioning

confidence: 99%

Efficient Mining Algorithm For Reducing Number Of Itemsets Using Chud

Hari.¹,

Suganya²

2016

IJECS

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“…Based on the MF algorithm concept raised by Chen et aL [2], the various users' references seed the maximal forward references. Supposed that the J user's maximal forward references include k sub-references, the maximal forward reference is…”

Section: Search For Maximal Forward Referencesmentioning

confidence: 99%

“…Chen et al [2] introduce the concept of Maximal Forward References which tries to divide the user's task into several transactions to extract user access pattern. This technique firstly converts the original sequence of web log data into a set of maximal forward references.…”

Section: \ Introductionmentioning

confidence: 99%

A HowNet Based Web Log Mining Algorithm

IFIP International Federation for Information Processing

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Web log mining is used to extract user access pattern. An algorithm is proposed in this ps^er to resolve the problem of bad explanation for page sequence of web log mining. The algorithm firstly transforms user visited page sequence into maximal forward sequence, and then uses HowNet based semantic similar algorithm to describe user interest in visit sequence and explains the interest movement with certain semantic words. The algorithm will help web sites provide personalization pages.

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Efficient Web Mining for Traversal Path Patterns

Cited by 33 publications

References 0 publications

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Efficient Mining Algorithm For Reducing Number Of Itemsets Using Chud

A HowNet Based Web Log Mining Algorithm

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