A Multi-channel Application Framework for Customer Care Service Using Best-First Search Technique

It has become imperative to find a solution to the dissatisfaction in response by mobile service providers when interacting with their customer care centres. Problems faced with Human to Human Interaction (H2H) between customer care centres and their customers include delayed response time, inconsistent solutions to questions or enquires and lack of dedicated access channels for interaction with customer care centres in some cases. This paper presents a framework and development techniques for a multi-channel application providing Human to System (H2S) interaction for customer care centre of a mobile telecommunication provider. The proposed solution is called Interactive Customer Service Agent (ICSA). Based on single-authoring, it will provide three media of interaction with the customer care centre of a mobile telecommunication operator: voice, phone and web browsing. A mathematical search technique called Best-First Search to generate accurate results in a search environmen

Staging Transformations for Multimodal Web Interaction Management

Multimodal interfaces are becoming increasingly ubiquitous with the advent of mobile devices, accessibility considerations, and novel software technologies that combine diverse interaction media. In addition to improving access and delivery capabilities, such interfaces enable flexible and personalized dialogs with websites, much like a conversation between humans. In this paper, we present a software framework for multimodal web interaction management that supports mixed-initiative dialogs between users and websites. A mixed-initiative dialog is one where the user and the website take turns changing the flow of interaction. The framework supports the functional specification and realization of such dialogs using staging transformations -- a theory for representing and reasoning about dialogs based on partial input. It supports multiple interaction interfaces, and offers sessioning, caching, and co-ordination functions through the use of an interaction manager. Two case studies are presented to illustrate the promise of this approach.Comment: Describes framework and software architecture for multimodal web interaction managemen

Holistic engineering design : a combined synchronous and asynchronous approach

To aid the creation and through-life support of large, complex engineering products, organizations are placing a greater emphasis on constructing complete and accurate records of design activities. Current documentary approaches are not sufficient to capture activities and decisions in their entirety and can lead to organizations revisiting and in some cases reworking design decisions in order to understand previous design episodes. Design activities are undertaken in a variety of modes; many of which are dichotomous, and thus each require separate documentary mechanisms to capture information in an efficient manner. It is possible to identify the modes of learning and transaction to describe whether an activity is aimed at increasing a level of understanding or whether it involves manipulating information to achieve a tangible task. The dichotomy of interest in this paper is that of synchronous and asynchronous working, where engineers may work alternately as part of a group or as individuals and where different forms of record are necessary to adequately capture the processes and rationale employed in each mode. This paper introduces complimentary approaches to achieving richer representations of design activities performed synchronously and asynchronously, and through the undertaking of a design based case study, highlights the benefit of each approach. The resulting records serve to provide a more complete depiction of activities undertaken, and provide positive direction for future co-development of the approaches

A Review of the "Digital Turn" in the New Literacy Studies

Digital communication has transformed literacy practices and assumed great importance in the functioning of workplace, recreational, and community contexts. This article reviews a decade of empirical work of the New Literacy Studies, identifying the shift toward research of digital literacy applications. The article engages with the central theoretical, methodological, and pragmatic challenges in the tradition of New Literacy Studies, while highlighting the distinctive trends in the digital strand. It identifies common patterns across new literacy practices through cross-comparisons of ethnographic research in digital media environments. It examines ways in which this research is taking into account power and pedagogy in normative contexts of literacy learning using the new media. Recommendations are given to strengthen the links between New Literacy Studies research and literacy curriculum, assessment, and accountability in the 21st century

Solving the G-problems in less than 500 iterations: Improved efficient constrained optimization by surrogate modeling and adaptive parameter control

Constrained optimization of high-dimensional numerical problems plays an important role in many scientific and industrial applications. Function evaluations in many industrial applications are severely limited and no analytical information about objective function and constraint functions is available. For such expensive black-box optimization tasks, the constraint optimization algorithm COBRA was proposed, making use of RBF surrogate modeling for both the objective and the constraint functions. COBRA has shown remarkable success in solving reliably complex benchmark problems in less than 500 function evaluations. Unfortunately, COBRA requires careful adjustment of parameters in order to do so. In this work we present a new self-adjusting algorithm SACOBRA, which is based on COBRA and capable to achieve high-quality results with very few function evaluations and no parameter tuning. It is shown with the help of performance profiles on a set of benchmark problems (G-problems, MOPTA08) that SACOBRA consistently outperforms any COBRA algorithm with fixed parameter setting. We analyze the importance of the several new elements in SACOBRA and find that each element of SACOBRA plays a role to boost up the overall optimization performance. We discuss the reasons behind and get in this way a better understanding of high-quality RBF surrogate modeling

Machine Learning and Integrative Analysis of Biomedical Big Data.

Recent developments in high-throughput technologies have accelerated the accumulation of massive amounts of omics data from multiple sources: genome, epigenome, transcriptome, proteome, metabolome, etc. Traditionally, data from each source (e.g., genome) is analyzed in isolation using statistical and machine learning (ML) methods. Integrative analysis of multi-omics and clinical data is key to new biomedical discoveries and advancements in precision medicine. However, data integration poses new computational challenges as well as exacerbates the ones associated with single-omics studies. Specialized computational approaches are required to effectively and efficiently perform integrative analysis of biomedical data acquired from diverse modalities. In this review, we discuss state-of-the-art ML-based approaches for tackling five specific computational challenges associated with integrative analysis: curse of dimensionality, data heterogeneity, missing data, class imbalance and scalability issues