Web usage mining with evolutionary extraction of temporal fuzzy association rules

Matthews, Stephen G.; Góngora, Mario; Hopgood, Adrian A.; Ahmadi, Samad

doi:10.1016/j.knosys.2013.09.003

Cited by 41 publications

(15 citation statements)

References 33 publications

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“…5: The fuzzy set Fi j [27,29] of the quantitative value Vi j of the j th webpage pj in a Ti can be represented by the given membership functions for the webpage pz as:…”

Section: Defmentioning

confidence: 99%

High Fuzzy Utility Strategy Based Webpage Sets Mining from Weblog Database

Kumar¹,

Thakur²

2018

IJIES

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Fuzzy utility mining has been an emerging research issue because of its comprehensibility and fitting to real data sets. Various researches such as association rules mining (ARM), frequent pattern, fuzzy based frequent pattern and utility based frequent pattern mining have been carried out. However, there has been a little research focusing on fuzzy utility based webpage sets mining from weblog databases. Hence, this work high fuzzy utility based webpage sets mining (HFUBWSM) contributes in developing an efficient fuzzy utility strategy to discover frequent webpage sets from web log database. Here, downward closure property in fuzzy sets is applied for pruning the large space by minimum fuzzy utility threshold value (MFUTV) and user defined percentile (UDP). The Experimental evaluation shows that HFUBWSM outperforms the existing algorithms-IHUP, UP-Growth, FHM and HUI-Miner in terms of running time and memory consumption.

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“…5: The fuzzy set Fi j [27,29] of the quantitative value Vi j of the j th webpage pj in a Ti can be represented by the given membership functions for the webpage pz as:…”

Section: Defmentioning

confidence: 99%

High Fuzzy Utility Strategy Based Webpage Sets Mining from Weblog Database

Kumar¹,

Thakur²

2018

IJIES

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“…However, most of the association rule mining methods did not consider the ambiguity of data in the process of data pre-processing stage that cannot reflect the representative of data and human's cognition completely and truly (Kuok et al, 1998;Kaya & Alhajj, 2003;Weng, 2011;Matthews et al, 2013;Wang et al, 2015). Therefore, converting the data into linguistic data by using fuzzy sets has become an important research direction for the data mining application (Ashish & Vikramkumar, 2010;Weng, 2011;Sowan et al, 2013;Jin et al, 2014;Arafah & Mukhlash, 2015;Palacios et al, 2015;Khatib et al, 2015).…”

Section: Contribution Of This Paper To the Literaturementioning

confidence: 99%

A Study on the Rare Factors Exploration of Learning Effectiveness by Using Fuzzy Data Mining

Chen

Chang

2017

EURASIA J MATH SCI T

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The phenomenon of low fertility has been negative impacted on the social structure of the educational environment in Taiwan. To increase the learning effectiveness of students became the most important issue for the Universities in Taiwan. Due to the subjective judgment of evaluators and the attributes of influenced factors are always fuzzy, it is not easy to measure the learning effectiveness by using the crisp values for the qualitative factors. In additional, the negative behaviors or the infrequent learning data (rare item sets) cannot easily excavate from educational database. Therefore, a systematic mining method is proposed here by combining fuzzy set theory with data mining technology to explore the key factors of learning effectiveness from the infrequent data. A case study implemented in this paper and showed that the proposed method can effectively find the important factors and valuable patterns from the survey data. The results of this paper can provide the important information for teachers to help students increase the learning effectiveness. Finally, the conclusions are addressed at the end of this paper.

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“…S. G. Matthews et al, introduced hereditary calculation (GA)-based arrangement is depicted that uses the versatile way of the 2-tuple phonetic outline to find decides that happen at the crossing point of fluffy set fringes. The GA-based progress is upgraded from past work by including a chart outline and a superior wellness work [8].…”

Section: Applications Of Web Usage Miningmentioning

confidence: 99%

A Review on Clustering Techniques

Kumar¹

2017

International Journal of Recent Advancement in Engineering &Amp; Research

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Abstract-The World Wide Web keeps on developing vault of site pages and connections at an exponential rate which makes abusing all valuable data a standing test. It has as of late an extensive variety of uses in E-trade site and E-administrations, for example, building intelligent showcasing systems, Web proposal and Web personalization. Web utilization mining is the way toward separating helpful use designs from the web information. Web personalization utilizes web utilization digging strategy for the procedure of information obtaining done by investigating the client navigational examples premium. These days, the Web is an essential wellspring of data recovery, and the clients getting to the Web are from various foundations. The use data about clients is recorded in web logs. Examining web log documents to extricate helpful examples is called Web Usage Mining. Web use mining approaches incorporate bunching, affiliation lead mining, successive example mining and so forth. This article gives a study of the accessible writing on Web utilization mining and audits the exploration and application issues in web use mining.

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Web usage mining with evolutionary extraction of temporal fuzzy association rules

Cited by 41 publications

References 33 publications

High Fuzzy Utility Strategy Based Webpage Sets Mining from Weblog Database

High Fuzzy Utility Strategy Based Webpage Sets Mining from Weblog Database

A Study on the Rare Factors Exploration of Learning Effectiveness by Using Fuzzy Data Mining

A Review on Clustering Techniques

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