13205673
Automatic Generation of Domain Models for Call-Centers from Noisy Transcriptions
Call centers handle customer queries from various domains such as computer sales and support, mobile phones, car rental, etc. Each such domain generally has a domain model which is essential to handle customer complaints. These models contain common problem categories, typical customer issues and their solutions, greeting styles. Currently these models are manually created over time. Towards this, we propose an unsupervised technique to generate domain models automatically from call transcriptions. We use a state of the art Automatic Speech Recognition system to transcribe the calls between agents and customers, which still results in high word error rates (40%) and show that even from these noisy transcriptions of calls we can automatically build a domain model. The domain model is comprised of primarily a topic taxonomy where every node is characterized by topic(s), typical Questions-Answers (Q&As), typical actions and call statistics. We show how such a domain model can be used for topic identification of unseen calls. We also propose applications for aiding agents while handling calls and for agent monitoring based on the domain model.
54110472
Fast and Accurate Text Classification via Multiple Linear Discriminant Projections
Publisher Summary 
Text classification is a standard problem in information retrieval (IR). A learner is presented with training documents, each labeled as containing or not containing material relevant to a given topic. Support vector machines (SVMs) have shown superb performance for text classification tasks. They are accurate, robust, and quick to apply to test instances. Their only potential drawback is their training time and memory requirement. SVMs have been trained on data sets with several thousand instances, but Web directories today contain millions of instances that are valuable for mapping billions of Web pages into Yahoo!-like directories. This chapter presents Simple Iterative Multiple Projection on Lines (SIMPL), a nearly linear-time classification algorithm that mimics the strengths of SVMs while avoiding the training bottleneck. It uses Fisher's linear discriminant, a classical tool from statistical pattern recognition, to project training instances to a carefully selected low-dimensional subspace before inducing a decision tree on the projected instances. SIMPL uses efficient sequential scans and sorts, and is comparable in speed and memory scalability to widely used naive Bayes (NB) classifiers, but it beats NB accuracy decisively.
14820946
A hierarchical monothetic document clustering algorithm for summarization and browsing search results
Organizing Web search results into a hierarchy of topics and sub-topics facilitates browsing the collection and locating results of interest. In this paper, we propose a new hierarchical monothetic clustering algorithm to build a topic hierarchy for a collection of search results retrieved in response to a query. At every level of the hierarchy, the new algorithm progressively identifies topics in a way that maximizes the coverage while maintaining distinctiveness of the topics. We refer the proposed algorithm to as DisCover. Evaluating the quality of a topic hierarchy is a non-trivial task, the ultimate test being user judgment. We use several objective measures such as coverage and reach time for an empirical comparison of the proposed algorithm with two other monothetic clustering algorithms to demonstrate its superiority. Even though our algorithm is slightly more computationally intensive than one of the algorithms, it generates better hierarchies. Our user studies also show that the proposed algorithm is superior to the other algorithms as a summarizing and browsing tool.
27759262
Automatic categorization of web sites based on source types
An important issue with the Web is verification of the accuracy, currency and authenticity of the information associated with Web sites. One way to address this problem is to identify the "source" or "sponsor" of the Web site. However, source identification is non-trivial because the source of a Web site cannot always be determined by the URL or content of the site. In this paper, we propose a method for source identification that uses various types of inbound, outbound and internal interactions that arise due to hyperlinks between and within Web sites.
9104858
Moment-Linear Stochastic Systems
We introduce a class of quasi-linear models for stochastic dynamics, called moment-linear stochastic systems (MLSS). We formulate MLSS and analyze their dynamics, as well as discussing common stochastic models that can be represented as MLSS. Further studies, including development of optimal estimators and controllers, are summarized. We discuss the reformulation of a common stochastic hybrid system—the Markovian jump- linear system (MJLS)—as an MLSS, and show that the MLSS formulation can be used to develop some new analyses for MJLS. Finally, we briefly discuss the use of MLSS in modeling certain stochastic network dynamics. Our studies suggest that MLSS hold promise in providing a framework for modeling interesting stochastic dynamics in a tractable manner.
34607469
On the Coleman indices of voting power
Coleman [1971. Control of collectives and the power of a collectivity to act. In: Lieberman, B. (Ed.), Social Choice. Gordon and Breach, New York, pp. 269-298] suggested two indices of voting power, power to prevent an action and power to initiate an action. This paper rigorously demonstrates relationship between the two indices and shows that they satisfy several attractive properties.
10991562
Strings: a high-performance distributed shared memory for symmetrical multiprocessor clusters
Introduces Strings, a high-performance distributed shared memory system designed for clusters of symmetrical multiprocessors (SMPs). The distinguishing feature of this system is the use of a fully multithreaded runtime system, written using POSIX threads. Strings also allows multiple application threads to be run on each node in a cluster. Since most modern UNIX systems can multiplex these threads on kernel-level lightweight processes, applications written using Strings can use all the processors in a SMP machine. This paper describes some of the architectural details of the system and analyzes the performance improvements with two example programs and a few benchmark programs from the SPLASH-2 suite.
2670464
Grid graph reachability problems
We study the complexity of reachability problems on various classes of grid graphs. Reachability on certain classes of grid graphs gives natural examples of problems that are hard for NC1 under AC0 reductions but are not known to be hard far L; they thus give insight into the structure of L. In addition to explicating the structure of L, another of our goals is to expand the class of digraphs for which connectivity can be solved in logspace, by building on the work of Jakoby et al. (2001), who showed that reachability in series-parallel digraphs is solvable in L. We show that reachability for single-source multiple sink planar dags is solvable in L
11274155
Minimum-Energy Broadcast Using Practical Directional Antennas in All-Wireless Networks
Energy-efficient broadcast communication is an important problem in wireless ad hoc networks. Previously, minimum-energy broadcast that exploits the broadcast nature of radio transmission has been studied and shown to be NP-complete for omnidirectional antennas. In this paper, we investigate the minimum-energy broadcast problem under a wide spectrum of directional antenna models, including sectored antennas with fixed sectors and beamwidth and antenna array-based smart antennas with varying degrees of beam orientation and beamwidth. We first propose the RF design and implementation of each model, which suggests the practical parameters of antennas under that model. We then show that the minimum-energy broadcast problem under each of the antenna models is NP-complete. Lastly, we present a heuristic algorithm based on BIP for the above problem under each directional antenna model and experimentally compare the energy efficiency of using different directional antennas using these heuristics. Our results show that using antennas with adjustable orientation and variable beamwidth gives the best results. For such antennas, the scanning angle is the dominant factor in improving the quality of the broadcast trees. The number of antennas per node is not that critical to obtaining a better broadcast tree as long as it is large enough to cover the entire 360◦ around a node so as to prevent network partitioning.