Shyam Boriah

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Measuring similarity or distance between two entities is a key step for several data mining and knowledge discovery tasks. The notion of similarity for continuous data is relatively well-understood, but for categorical data, the similarity computation is not straightforward. Several data-driven similarity measures have been proposed in the literature to(More)
The study of land cover change is an important problem in the Earth Science domain because of its impacts on local climate, radiation balance, biogeochemistry, hydrology, and the diversity and abundance of terrestrial species. Most well-known change detection techniques from statistics, signal processing and control theory are not well-suited for the(More)
The climate and earth sciences have recently undergone a rapid transformation from a data-poor to a data-rich environment. In particular, climate and ecosystem related observations from remote sensors on satellites, as well as outputs of climate or earth system models from large-scale computational platforms, provide terabytes of temporal, spatial and(More)
It is well-known that forests play a vital role in maintaining biodiversity and the health of ecosystems across the Earth. This important ecological resource is under threat from both anthropogenic and biogenic pressures, ranging from insect infestations to commercial logging. Detecting, quantifying and reporting the magnitude of forest degradation are(More)
Land cover change, especially deforestation, is a priority issue for policymakers at the local, national and international scale. Deforestation’s contribution of up to 20% of global greenhouse gas emissions is already well known; the loss of biodiversity from land conversion is also well established [7, 13]. Policymakers at the UN Framework Convention on(More)
Forests are a critical component of the planet's ecosystem. Unfortunately, there has been significant degradation in forest cover over recent decades as a result of logging, conversion to crop, plantation, and pasture land, or disasters (natural or man made) such as forest fires, floods, and hurricanes. As a result, significant attention is being given to(More)
Segmentation of a time series attempts to divide it into homogeneous subsequences, such that each of these segments are different from each other. A typical segmentation framework involves selecting a model that is used to represent the segment. In this paper, we investigate segmentation scores based on difference between models and propose two approaches(More)
Time series data are common in a variety of fields ranging from economics to medicine and manufacturing. As a result, time series analysis and modeling has become an active research area in statistics and data mining. In this paper, we focus on a type of change we call contextual time series change (CTC) and propose a novel two-stage algorithm to address(More)