A load estimation algorithm based on k-means cluster analysis was developed. The algorithm applies cluster centres – of previously clustered load profiles – and distance functions to estimate missing and future measurements. Canberra, Manhattan, Euclidean, and Pearson correlation distances were investigated. Several case studies were implemented using daily and segmented load profiles of aggreg...

The dilation-free graph of a planar point set S is a graph that spans S in such a way that the distance between two points in the graph is no longer than their planar distance. Metrically speaking, those graphs are equivalent to complete graphs; however they have far fewer edges when considering the Manhattan distance (we give here an upper bound on the number of saved edges). This article prov...

Proof. We first prove that every free cell accessible from s becomes a frontier at least once. We prove this by induction on the Manhattan distance d of the cells from s. As the base case, consider d = 0. The only cell with d = 0 is s itself, and it is added to the frontier set F in line 3 of OnlineCoverage. We now assume correctness for d = k and prove for d = k + 1. Consider a cell c with dis...

Clustering web users based on their access patterns is a quite significant task in Web Usage Mining. Further to clustering it is important to evaluate the resulted clusters in order to choose the best clustering for a particular framework. This paper examines the usage of Kullback-Leibler divergence, an information theoretic distance, in conjuction with the k-means clustering algorithm. It comp...

In recent years, the research cluster of objective interestingness measures has rapidly developed in order to assist users to choose the appropriate measure for their application. Researchers in this field mainly focus on three main directions: clustering based on the properties of the measures, clustering based on the behavior of measures and clustering tendency of variation in statistical imp...

Marcellus M. Caldas, Matthew R. Sanderson, Martha Mather, Melinda D. Daniels, Jason S. Bergtold, Joseph Aistrup, Jessica L. Heier Stamm, David Haukos, Kyle Douglas-Mankin, Aleksey Y. Sheshukov, and David Lopez-Carr Department of Geography, Kansas State University, Manhattan, KS 66506; Department of Sociology, Anthropology, and Social Work, Kansas State University, Manhattan, KS 66506; US Geolog...

Temporal queries on time evolving data are at the heart of a broad range of business and network intelligence applications ranging from consumer behavior analysis, trend analysis, temporal pattern mining, sentiment analysis on social media, cyber security, and network monitoring. In this work, we present an innovative data structure called Fast Approximate Query-able(FAQ), which provides a unif...

Document retrieval is the process of matching of some sated user query against a set of free-text records (documents), its one major technique for organizing and managing information. This project was concerned with studying which of the different statistical measures in IR have the most effectiveness on document retrieval using a unified set of documents. The results show that the Cosine Simil...