Evaluation of Reranked Recommended Queries in Web Information Retrieval using NDCG and CV

Umagandhi, R.; Kumar, Ashwani

doi:10.5815/ijitcs.2015.08.04

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…Since its appearance, the Web has not stopped evolving by integrating more and more services for customers who are becoming more and more numerous. The new generation of the web called the Semantic Web promises to provide an environment for translating the structure of web pages into meaningful content [2]. This will be possible through the work carried out in the field of IE.…”

Section: Context and Issuesmentioning

confidence: 99%

Dynamic Editing Distance-based Extracting Relevant Information Approach from Social Networks

Omri¹,

Fkih²

2022

IJCNIS

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Online social networks, such as Facebook, Twitter, LinkedIn, etc., have grown exponentially in recent times with a large amount of information. These social networks have huge volumes of data especially in structured, textual, and unstructured forms which have often led to cyber-crimes like cyber terrorism, cyber bullying, etc., and extracting information from these data has now become a serious challenge in order to ensure the data safety. In this work, we propose a new, supervised approach for Information Extraction (IE) from Web resources based on remote dynamic editing, called EIDED. Our approach is part of the family of IE approaches based on masks extraction and is articulated around three algorithms: (i) a labeling algorithm, (ii) a learning and inference algorithm, and (iii) an extended edit distance algorithm. Our proposed approach is able to work even in the presence of anomalies in the tuples such as missing attributes, multivalued attributes, permutation of attributes, and in the structure of web pages. The experimental study, which we conducted, on a standard database of web pages, shows the performance of our EIDED approach compared to approaches based on the classic edit distance, and this with respect to the standard metrics recall coefficient, precision, and F1-measure.

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Section: Context and Issuesmentioning

confidence: 99%

Dynamic Editing Distance-based Extracting Relevant Information Approach from Social Networks

Omri¹,

Fkih²

2022

IJCNIS

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“…Cumulative gain indexes commonly used in the field of information retrieval are used to evaluate the matching results, and the average of the five evaluation results is used as the final evaluation index, expressed as η. Where, the larger the average value, the more accurate the matching result is (Wang et al, 2014;Umagandhi and Senthil Kumar, 2015).…”

Section: Case Analysismentioning

confidence: 99%

Intelligent Filling Method of Power Grid Working Ticket Based on Historical Ticket Knowledge Base

Liu

et al. 2021

Front. Energy Res.

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The traditional power grid ticket filling method has a large workload, low efficiency, and cannot achieve comprehensive and effective reference of historical tickets. This paper proposes a method of intelligent filling in a power grid working ticket based on a historical ticket knowledge base. Firstly, the historical ticket data are preprocessed, then the historical ticket information is mined by the association rule algorithm, and the method of establishing the historical ticket knowledge base is proposed. Based on the improved word bag model, an intelligent grid work ticket filling model is established based on the historical ticket knowledge base, and the correctness of the method is verified by an example. The results show that the accuracy of the proposed method is at least 18% higher than that of the traditional model, and the matching efficiency is 50% higher than the evaluation results of the three models based on semantic expressions. The method enables the identification and extraction of similar and associated work tickets, improves the efficiency of filling work tickets for power grids, and promotes the intelligence of the safety procedures for power grid operations.

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Domain Based Web Retrieval Driven by Semantic Representation of Personal Knowledge Organizer

2016

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One important aspect in self-directed learning is to find learning resources, which can be referenced from the Internet. In the process of finding the resources, users have experience in accessing certain sites for specific information. But, when they want to refer back to related information, usersare supposed to recall the domain of sites and to determine the proportion of priority on a number of sites. The experience of accessing the Internet is mapped into semantic representation of Knowledge Organization (KO) like a memory thatit can be exploited to support in gaining new resources in the same domain of knowledge. This study aims to develop a web retrieval application to assist users based on their experience. The application will identify the domains of the sites that were previously accessed by tracing the representation. The domains are used as references to direct the search. Searching the web resources is undertaken by the composition of domain based search and search without domain limitation. The composition ofboth searchescan be determined by the users according to their expectations. The domain based search composition is determined by the resourcecontributions within the scope of a knowledge domain. The test results show that the system is able to identify the domain’s location and the proportions as preferences for searching. The performance of the system in searching shows thatthe query returnsof relevant documents are dominant.

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Evaluation of Reranked Recommended Queries in Web Information Retrieval using NDCG and CV

Cited by 3 publications

References 18 publications

Dynamic Editing Distance-based Extracting Relevant Information Approach from Social Networks

Dynamic Editing Distance-based Extracting Relevant Information Approach from Social Networks

Intelligent Filling Method of Power Grid Working Ticket Based on Historical Ticket Knowledge Base

Domain Based Web Retrieval Driven by Semantic Representation of Personal Knowledge Organizer

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