Showing papers by "Sameep Mehta published in 2016"

Assessing Value of One or More Data Sets in the Context of a Set of Applications

Abstract: Methods, systems, and computer program products for assessing value of one or more data sets in the context of a set of applications are provided herein. A computer-implemented method includes selecting analytic applications of interest based on a characterization of data attributes of each of the available data sets; automatically determining an impact of each of the data attributes of each of the available data sets on an end value of each of the analytic applications of interest; automatically computing an amount of improvement to the end value of each of the analytic applications of interest based on inclusion of an additional data set; and automatically determining a value attributed to the additional data set based on a comparison of (i) the cost of adding the additional data set to the available data sets to (ii) the computed amount of improvement based on the inclusion of the additional data set.

Select, Link and Rank: Diversified Query Expansion and Entity Ranking Using Wikipedia

Abstract: A search query, being a very concise grounding of user intent, could potentially have many possible interpretations. Search engines hedge their bets by diversifying top results to cover multiple such possibilities so that the user is likely to be satisfied, whatever be her intended interpretation. Diversified Query Expansion is the problem of diversifying query expansion suggestions, so that the user can specialize the query to better suit her intent, even before perusing search results. We propose a method, Select-Link-Rank, that exploits semantic information from Wikipedia to generate diversified query expansions. SLR does collective processing of terms and Wikipedia entities in an integrated framework, simultaneously diversifying query expansions and entity recommendations. SLR starts with selecting informative terms from search results of the initial query, links them to Wikipedia entities, performs a diversity-conscious entity scoring and transfers such scoring to the term space to arrive at query expansion suggestions. Through an extensive empirical analysis and user study, we show that our method outperforms the state-of-the-art diversified query expansion and diversified entity recommendation techniques.

Multi-level colocation and processing of spatial data on MapReduce

Abstract: Methods, systems, and computer program products for multi-level colocation and analytical processing of spatial data on MapReduce are provided herein. A method includes correlating multiple items of spatial data and multiple items of attribute data within a file system to generate multiple blocks of correlated data; colocating each of the multiple blocks of correlated data on a given node within the file system based on a data block placement policy; and clustering multiple replicas generated for each of the multiple data blocks at multiple levels of spatial granularity within the file system.

Compensating for reduced availability of a disrupted project resource

Abstract: A method and associated systems for automatically identifying critical resources in an organization. An organization creates a model of the dependencies between pairs of resource types, wherein that model describes how the organization's projects and services are affected when a resource type becomes unavailable. This model may include a system of directed graphs. This model may be used to automatically identify a resource type as critical if unacceptable cost is incurred by resuming projects and services rendered infeasible when the resource type is disrupted. The model may also be used to automatically identify a first resource type as critical for a second resource type when disruption of the first resource type forces the available capacity of the second resource type to fall below a threshold value.