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Authors:Malhotra; Diksha, Bhatia, Rajesh, Kumar, Manish Pages: 1 - 13 Abstract: The deep web is comprised of a large corpus of information hidden behind the searchable web interfaces. Accessing content through searchable interfaces is somehow a challenging task. One of the challenges in accessing the deep web is automatically filling the searchable web forms for retrieving the maximum number of records by a minimum number of submissions. The paper proposes a methodology to improve the existing method of getting informative data behind searchable forms by automatically submitting web forms. The form text field values are obtained through Bayesian inferences. Using Bayesian networks, the authors aim to infer the values of text fields using the existing values in the label value set (LVS) table. Various experiments have been conducted to measure the accuracy and computation time taken by the proposed value selection method. It proves to be highly accurate and takes less computation time than the existing term frequency-inverse document frequency (TF-IDF) method, hence increasing the performance of the crawler. Keywords: Information Retrieval; Library & Information Science; Information Retrieval Citation: International Journal of Information Retrieval Research (IJIRR), Volume: 13, Issue: 1 (2023) Pages: 1-13 PubDate: 2023-01-01T05:00:00Z DOI: 10.4018/IJIRR.318399 Issue No:Vol. 13, No. 1 (2023)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:Agarwal; Reshu, Dixit, Adarsh Pages: 1 - 14 Abstract: This paper presents a comparative research study between a number of data mining techniques, knowledge discovery tools, data analysis and software packages to be used in a Decision Support System (DSS) for Smart water supply chain resources management. The case study deals with the evaluation and comparative research of water quality of city water supply within New Delhi city area. In the case of New-Delhi water supply alternative actions for improving of water supply and quality are defined for efficient supply in distributed area. The real time water quality monitor uses given standards by Water Quality Index (WQI) and Statistical analysis done on it suggests the shortest path between supply station and local area distribution Centre by used WEKA mining tool (decision tree) and OLAP. The results show that the city water isn't supplied efficiently in the city and not within the standard quality criteria of (WHO) standards and Indian standards. Leanings and research challenges observed during this comparative study have also been enumerated. Keywords: Information Retrieval; Library & Information Science; Information Retrieval Citation: International Journal of Information Retrieval Research (IJIRR), Volume: 13, Issue: 1 (2023) Pages: 1-14 PubDate: 2023-01-01T05:00:00Z DOI: 10.4018/IJIRR.317087 Issue No:Vol. 13, No. 1 (2023)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:B. Subbulakshmi, C. Deisy, Parthasarathy S. Pages: 1 - 21 Abstract: Associative classification (AC) performs much better than other traditional classifiers. It generates a huge number of class association rules (CARs). Since users are interested in the subset of rules, constraints are introduced in the generation of CARs. Real-world databases are record-based in which data is continuously added which demands incremental mining. Hence, constraint class association rules (CCAR) is mined from incremental data. To limit the number of rules and to remove the duplicate rules, redundant rule pruning and duplicate rule pruning techniques are applied. To improve the accuracy of the classifier, the rule selection using principality metric has been applied and the classifier is constructed with rules possessing high principality. Then, classifier is evaluated using single rule and multiple rule prediction methods and the accuracy of the proposed classifier are measured. Experimental results show that the accuracy of the proposed classifier is relatively higher when compared to other algorithms. Keywords: Information Retrieval; Library & Information Science; Information Retrieval Citation: International Journal of Information Retrieval Research (IJIRR), Volume: 13, Issue: 1 (2023) Pages: 1-21 PubDate: 2023-01-01T05:00:00Z DOI: 10.4018/IJIRR.316125 Issue No:Vol. 13, No. 1 (2023)
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