Clustering with the DBLP Bibliography to Measure External Impact of a Computer Science Research Area
نویسندگان
چکیده
Digital bibliometric databases are rich sources of knowledge to understand the connections between authors and conferences. The DBLP Computer Science Bibliography is one of the main repositories for the computer science community. However, understanding and interpreting the bibliographic information is not intuitive and at times, controversial [14]. How should one determine a researcher’s area? What can we learn from the interactions between authors in each area?
منابع مشابه
Clustering with Intelligent Linexk-Means
The intelligent LINEX k-means clustering is a generalization of the k-means clustering so that the number of clusters and their related centroid can be determined while the LINEX loss function is considered as the dissimilarity measure. Therefore, the selection of the centers in each cluster is not randomly. Choosing the LINEX dissimilarity measure helps the researcher to overestimate or undere...
متن کاملExtraction of Respiratory Signal Based on Image Clustering and Intensity Parameters at Radiotherapy with External Beam: A Comparative Study
Background: Since tumors located in thorax region of body mainly move due to respiration, in the modern radiotherapy, there have been many attempts such as; external markers, strain gage and spirometer represent for monitoring patients’ breathing signal. With the advent of fluoroscopy technique, indirect methods were proposed as an alternative approach to extract patients’ breathing signals...
متن کاملA Survey Of Approaches To Automatic Schema Matching Dblp
In this paper we propose a method for automatic discovery of identity relationship Ley, M.: The DBLP Computer Science Bibliography: Evolution, Research Issues, Shvaiko, P., Euzenat, J.: A Survey of Schema-based Matching Approaches. Ontology-Based Method for Schema Matching in a Peer-to-Peer Database System. BNCOD Parallel query optimization methods and approaches: a survey. Guest Editors Ontolo...
متن کاملAn Empirical Comparison of Distance Measures for Multivariate Time Series Clustering
Multivariate time series (MTS) data are ubiquitous in science and daily life, and how to measure their similarity is a core part of MTS analyzing process. Many of the research efforts in this context have focused on proposing novel similarity measures for the underlying data. However, with the countless techniques to estimate similarity between MTS, this field suffers from a lack of comparative...
متن کاملImproved Automatic Clustering Using a Multi-Objective Evolutionary Algorithm With New Validity measure and application to Credit Scoring
In data mining, clustering is one of the important issues for separation and classification with groups like unsupervised data. In this paper, an attempt has been made to improve and optimize the application of clustering heuristic methods such as Genetic, PSO algorithm, Artificial bee colony algorithm, Harmony Search algorithm and Differential Evolution on the unlabeled data of an Iranian bank...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2014