List of Articles Web mining

• Open Access Article
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  1 - Product purchasing prediction in an online store by designing an artificial neural network using clickstream data
  Mahbube Mottaghi
  One of the key capabilities of competitive online stores is the effective prediction of customer buying as much as possible to apply customer service strategies to convert users to buyers and to increase sales rates. Data mining and artificial intelligence techniques ar More

  One of the key capabilities of competitive online stores is the effective prediction of customer buying as much as possible to apply customer service strategies to convert users to buyers and to increase sales rates. Data mining and artificial intelligence techniques are successful in categorizing and forecasting. Work has been proven in timely systems, such as e-commerce sites. In this paper, we propose a non-post-error neural network model with the aim of predicting purchases at user active stages in an online store. The training and evaluation of the neural network was performed using a set of revised sessions from server logs. The accuracy and retrieval power of the proposed neural network is 8999.79% and 89.696%, which indicates the high ability of this network (about 90%) in predicting the purchase Manuscript profile
• Open Access Article
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  2 - A Semantic Approach to Person Profile Extraction from Farsi Web Documents
  Hojjat Emami Hossein Shirazi ahmad abdolahzade
  10.7508/jist.2016.04.004
  Entity profiling (EP) as an important task of Web mining and information extraction (IE) is the process of extracting entities in question and their related information from given text resources. From computational viewpoint, the Farsi language is one of the less-studie More

  Entity profiling (EP) as an important task of Web mining and information extraction (IE) is the process of extracting entities in question and their related information from given text resources. From computational viewpoint, the Farsi language is one of the less-studied and less-resourced languages, and suffers from the lack of high quality language processing tools. This problem emphasizes the necessity of developing Farsi text processing systems. As an element of EP research, we present a semantic approach to extract profile of person entities from Farsi Web documents. Our approach includes three major components: (i) pre-processing, (ii) semantic analysis and (iii) attribute extraction. First, our system takes as input the raw text, and annotates the text using existing pre-processing tools. In semantic analysis stage, we analyze the pre-processed text syntactically and semantically and enrich the local processed information with semantic information obtained from a distant knowledge base. We then use a semantic rule-based approach to extract the related information of the persons in question. We show the effectiveness of our approach by testing it on a small Farsi corpus. The experimental results are encouraging and show that the proposed method outperforms baseline methods. Manuscript profile