Developing an intelligent trip recommender system by data mining methods

Data mining extracts hidden information from a database that the user did not know existed. Biclustering is one of the data mining technique which helps marketing user to target marketing campaigns more accurately and to align campaigns more closely with the needs, wants, and attitudes of customers and prospects. The biclustering results can be tuned to find users’ browsing patterns relevant to current business problems. This paper presents a new application of biclustering to web usage data using a combination of heuristics and meta-heuristics algorithms. Two-way K-means clustering is used to generate the seeds from preprocessed web usage data, Greedy Heuristic is used iteratively to refine a set of seeds, which is fast but often yield local optimal solutions. In this paper, Genetic Algorithm is used as a global optimizer that can be coupled with greedy method to identify the global optimal target user groups based on their coherent browsing pattern. The performance of the proposed work is evaluated by conducting experiment on the msnbc, a clickstream dataset from UCI repository. Results show that the proposed work performs well in extracting optimal target users groups from the web usage data which can be used for focalized marketing campaigns.

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Extraction of Target User Group from Web Usage Data Using Evolutionary Biclustering Approach

International Journal of Applied Metaheuristic Computing ◽

10.4018/jamc.2011070104 ◽

2011 ◽

Vol 2 (3) ◽

pp. 69-79 ◽

Cited By ~ 2

Author(s):

R. Rathipriya ◽

K. Thangavel ◽

J. Bagyamani

Keyword(s):

Data Mining ◽

Greedy Heuristic ◽

Data Mining Technique ◽

Web Usage ◽

Target User ◽

Global Optimizer ◽

User Groups ◽

Optimal Target ◽

Global Optimal ◽

Usage Data

Data mining extracts hidden information from a database that the user did not know existed. Biclustering is one of the data mining technique which helps marketing user to target marketing campaigns more accurately and to align campaigns more closely with the needs, wants, and attitudes of customers and prospects. The biclustering results can be tuned to find users’ browsing patterns relevant to current business problems. This paper presents a new application of biclustering to web usage data using a combination of heuristics and meta-heuristics algorithms. Two-way K-means clustering is used to generate the seeds from preprocessed web usage data, Greedy Heuristic is used iteratively to refine a set of seeds, which is fast but often yield local optimal solutions. In this paper, Genetic Algorithm is used as a global optimizer that can be coupled with greedy method to identify the global optimal target user groups based on their coherent browsing pattern. The performance of the proposed work is evaluated by conducting experiment on the msnbc, a clickstream dataset from UCI repository. Results show that the proposed work performs well in extracting optimal target users groups from the web usage data which can be used for focalized marketing campaigns.

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Inventory, Conservation Statement and Classification of Bird Trade in Cianjur based on Data Mining Methods

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b1005.0782s719 ◽

2019 ◽

Vol 8 (2S7) ◽

pp. 22-24

Keyword(s):

Data Mining ◽

Conservation Status ◽

Bird Species ◽

Dominance Status ◽

Rule Based ◽

Search Results ◽

The Status ◽

Mining Methods ◽

Total Species

Currently in the community many who keep birds. To get the birds people are looking for in the bird market. Total species of birds traded (Kabupaten Cianjur) as many as 46 types of 23 tribes. From the search results were found by IUCN endangered bird species but by law in Indonesia excluding protected ones such as the species of ekelgeling (Cissathalassina) whose conservation status is highly endangered. The excavation of the rule based on available data using the c45 algorithm shows that the dominance status of bird species in the Cipanas area has a significant influence on the status of the dominance of bird species for the entire Cianjur region.

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