Clustering of web search results based on the cuckoo search algorithm and Balanced Bayesian Information Criterion

Cobos, Carlos; Muñoz-Collazos, Henry; Urbano-Muñoz, Richar; Mendoza, Martha; León, Elizabeth; Herrera‐Viedma, Enrique

doi:10.1016/j.ins.2014.05.047

Cited by 97 publications

(35 citation statements)

References 55 publications

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“…Citespace was used for co-citation analysis [44]. Ucinet [45] and Vosviewer [46] were used for social network analysis and visualization and Carrot was used for cluster analysis [47]. Other tools such as Excel were also used for basic statistical analysis and visualization of the bibliometric results.…”

Section: Methodsmentioning

confidence: 99%

Visualizing the Academic Discipline of Knowledge Management

et al. 2018

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Abstract:The aim of this paper was to evaluate the research status of knowledge management (KM) and identify the characteristics of KM in the literature. We selected and studied in detail 7628 original research articles from the Web of Science from 1974 to 2017. Although many studies have contributed to the evolution of the KM domain, our results showed that a comprehensive bibliometric and visualization investigation was required. The literature on KM has grown rapidly since the 1970s. The United States of America, as the original contributing country, has also internationally collaborated the most in this field of study. The National Cheng Kung University has made the highest number of contributions. The majority of authors contributed a small number of publications. Additionally, the most common category in KM research was management. The main publications for KM research include Journal of Knowledge Management, and Knowledge Management Research & Practice. A keywords analysis determined that "knowledge sharing", "innovation", "ontology", and "knowledge management" were consistent hotspots in knowledge management research. Through a document co-citation analysis, the intellectual structures of knowledge management were defined, and four emerging trends were identified that focus on new phenomenon, the practice of knowledge management, small and medium enterprises (SMEs) management based on knowledge perspective, innovation and performance, and big data-enabled KM. We also provide eight research questions for future studies. Our results will benefit academics, researchers, and research students who want to rapidly obtain an overview of knowledge management research. This study can also be a starting point for communication between academics and practitioners.

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Section: Methodsmentioning

confidence: 99%

Visualizing the Academic Discipline of Knowledge Management

et al. 2018

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“…In the similar way, on comparison of precision parameter under evaluation for the proposed approach and existing approach WDC-CSK used by [23]the same dataset set is analyzed and results are plotted on the basis of precision, accuracy, recall and f-measure. The Table 3 presents the results being derived after execution.…”

Section: Resultsmentioning

confidence: 99%

An Improved Combined Content-similarity Approach for Optimizing Web Query Disambiguation

ShahidKama¹,

RolianaIbrahim

Ghani

2015

Journal of Internet Computing and Services

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The web search engines are exposed to the issue of uncertainty because of ambiguous queries, being input for retrieving the accurate results. Ambiguous queries constitute a significant fraction of such instances and pose real challenges to web search engines. Moreover, web search has created an interest for the researchers to deal with search by considering context in terms of location perspective. Our proposed disambiguation approach is designed to improve user experience by using context in terms of location relevance with the document relevance. The aim is that providing the user a comprehensive location perspective of a topic is informative than retrieving a result that only contains temporal or context information. The capacity to use this information in a location manner can be, from a user perspective, potentially useful for several tasks, including user query understanding or clustering based on location. In order to carry out the approach, we developed a Java based prototype to derive the contextual information from the web results based on the queries from the well-known datasets. Among those results, queries are further classified in order to perform search in a broad way. After the result provision to users and the selection made by them, feedback is recorded implicitly to improve the web search based on contextual information. The experiment results demonstrate the outstanding performance of our approach in terms of precision 75%, accuracy 73%; recall 81% and f-measure 78% when compared with generic temporal evaluation approach and furthermore achieved precision 86%, accuracy 71%; recall 67% and f-measure 75% when compared with web document clustering approach.

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“…The most popular clustering technique is kmeans clustering. K-means clustering is a data mining/machine learning algorithm used to cluster observations into groups of related observations without any prior knowledge of those relationships [13]. The k-means algorithm is one of the simplest clustering techniques and it is commonly used in data mining, biometrics and related fields [15].…”

Section: Module 3: Clusteringmentioning

confidence: 99%

Preprocessing of High Dimensional Dataset for Developing Expert IR System

Chaudhari¹,

Phadatare²,

Kudale³

et al. 2015

2015 International Conference on Computing Communication Control and Automation

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Now-a-days due to increase in the availability of computing facilities, large amount of data in electronic form is been generated. The data generated is to be analyzed inorder to maximize the benefit of intelligent decision making. Text categorization is an important and extensively studied problem in machine learning. The basic phases in the text categorization include preprocessing features like removing stop words from documents and applying TF-IDF is used which results into increase efficiency and deletion of irrelevant data from huge dataset. This paper discusses the implication of Information Retrieval system for text-based data using different clustering approaches. Applying TF-IDF algorithm on dataset gives weight for each word which summarized by Weight matrix.

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Clustering of web search results based on the cuckoo search algorithm and Balanced Bayesian Information Criterion

Cited by 97 publications

References 55 publications

Visualizing the Academic Discipline of Knowledge Management

Visualizing the Academic Discipline of Knowledge Management

An Improved Combined Content-similarity Approach for Optimizing Web Query Disambiguation

Preprocessing of High Dimensional Dataset for Developing Expert IR System

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