Acronym-Expansion Disambiguation for Intelligent Processing of Enterprise Information

An acronym is an abbreviation of several words in such a way that the abbreviation itself forms a pronounceable word. Acronyms occur frequently throughout various documents, especially those of a technical nature, for example, research papers and patents. While these acronyms can enhance document readability, in a variety of fields, they have a negative effect on business intelligence. To resolve this problem, we propose a method of acronym-expansion disambiguation to collect high-quality enterprise information. In experimental evaluations, we demonstrate its efficiency through the use of objective comparisons

Ontological Map of Service Oriented Architecture Based on Zachman

Service orientation is an approach in the field of enterprise architecture, business information systems and software application that its main element is the service. Shared services is an organization model of sharing, across an organization. It enables collaboration among the functions/departments. Main motivations for shared services are sharing, promote efficiency, reduce cost, and support scalability. Despite of the widespread use of these two approaches in information technology, there is no tool to optimize the management of them. The aim of this study is Ontological map of service oriented architecture based on zachman framework to adapt it in the reference enterprise architecture framework through implementation ontology views on system architect software and as well as equivalent ontology component with UML diagrams. After the implementation of the suggested model, the results showed that ontology is a formal description and explicit display of objects, concepts and other entities in the relationship between them. In other words, there is a model that describe all that is in fact in to understandable language for the system. Thus the proposed establishes have association between all aspects of zachman framework, also to create a clear description of business concepts in the management of shared services and is effective to provide a unified platform for enterprise modeling

An Ontological Framework for Context-Aware Collaborative Business Process Formulation

In cross-enterprise collaborative environment, we have dealt with challenges in business process integration for common business goals. Research directions in this domain range from business to business integration (B2Bi) to service-oriented augmentation. Ontologies are used in Business Process Management (BPM) to reduce the gap between the business world and information technology (IT), especially in the context of cross enterprise collaboration. For a dynamic collaboration, virtual enterprises need to establish collaborative processes with appropriate matching levels of tasks. However, the problem of solving the semantics mismatching is still not tackled or even harder in case of querying space between different enterprise profiles as considered as ontologies. This article presents a framework based on the ontological and context awareness during the task integration and matching in order to form collaborative processes in the manner of cross enterprise collaboration

Towards Efficient Locality Aware Parallel Data Stream Processing

Abstract: Parallel data processing and parallel streaming systems become quite popular. They are employed in various domains such as real-time signal processing, OLAP database systems, or high performance data extraction. One of the key components of these systems is the task scheduler which plans and executes tasks spawned by the application on available CPU cores. The multiprocessor systems and CPU architecture of the day become quite complex, which makes the task scheduling a challenging problem. In this paper, we propose a novel task scheduling strategy for parallel data stream systems, that reflects many technical issues of the current hardware. In addition, we have implemented a NUMA aware memory allocator that improves data locality in NUMA systems. The proposed task scheduler combined with the new memory allocator achieve up to 3× speed up on a NUMA system and up to 10% speed up on an older SMP system with respect to the unoptimized versions of the scheduler and allocator. Many of the ideas implemented in our parallel framework may be adopted for task scheduling in other domains that focus on different priorities or employ additional constraints

SEMANTIC SOCIAL NETWORK ANALYSIS FOR THE ENTERPRISE

Business processes are generally fixed and enforced strictly, as reflected by the static nature of underlying software systems and datasets. However, internal and external situations, organizational changes and various other factors trigger dynamism, which is reflected in the form of issues, complains, Q&A, opinions, reviews, etc, over a plethora of communication channels, such as email, chat, discussion forums, and internal social network. Careful and timely analysis and processing of such channels may lead to early detection of emerging trends, critical issues, opportunities, topics of interests, contributors, experts etc. Social network analytics have been successfully applied in general purpose, online social network platforms, like Facebook and Twitter. However, in order for such techniques to be useful in business context, it is mandatory to integrate them with underlying business systems, processes and practices. Such integration problem is increasingly recognized as Big Data problem. We argue that SemanticWeb technology applied with social network analytics can solve enterprise knowledge management, while achieving integration

Beating Social Pulse: Understanding Information Propagation via Online Social Tagging Systems

Abstract: Social media (e.g., Twitter and FaceBook) have been one of the most popular online communication channels to share information among users. It means the users can give (and have) cognitive influences to (and from) the others. Thus, it is important for many online collaborative applications to understand how the information can be propagated via such social media. In this paper, we focus on a social tagging system where users can easily exchange resources as well as their tags with other users. Given a certain tag from a temporal folksonomy, the social pulse can be established by counting the number of users (or resources). Particularly, we can discover meaningful relationship between tags by computing inducibility. To conduct experimentation, a tag search system has been implemented to collect a dataset from Flickr

Analyzing the Emergence of Semantic Agreement among Rational Agents

Todays complex online applications often require the interaction of multiple services that potentially belong to different business entities. Interoperability is a core element of such an environment, yet not a straightforward one. In this paper, we argue that the emergence of interoperability is an economic process among rational agents and, although interoperability can be mutually beneficial for the involved parties, it is also costly and may fail to emerge. As a sample scenario, we consider the emergence of semantic interoperability among rational service agents in the service-oriented architectures (SOA) and analyze their individual economic incentives with respect to utility, risk and cost. We model this process as a positive-sum game and study its equilibrium and evolutionary dynamics. According to our analysis, which is also experimentally verified, certain conditions on the communication cost, the cost of technological adaptation, the expected mutual benefit from interoperability as well as the expected loss from isolation drive the process

The Unification and Assessment of Multi-Objective Clustering Results of Categorical Datasets with H-Confidence Metric

Abstract: Multi objective clustering is one focused area of multi objective optimization. Multi objective optimization attracted many researchers in several areas over a decade. Utilizing multi objective clustering mainly considers multiple objectives simultaneously and results with several natural clustering solutions. Obtained result set suggests different point of views for solving the clustering problem. This paper assumes all potential solutions belong to different experts and in overall; ensemble of solutions finally has been utilized for finding the final natural clustering. We have tested on categorical datasets and compared them against single objective clustering result in terms of purity and distance measure of k-modes clustering. Our clustering results have been assessed to find the most natural clustering. Our results get hold of existing classes decided by human experts

On the emergence of semantic agreement among rational agents

Today’s complex online applications often require the interaction of multiple (web) services that belong to potentially different business entities. Interoperability is a core element of such an environment, yet not a straightforward one due to the lack of common data semantics. The problem is often approached by means of standardization procedures in a top-down manner with limited adoption in practice. (De facto) standards for semantic interoperability most commonly emerge in a bottom-up approach, i.e., involving the interaction and information exchange among self-interested industrial agents. In this paper, we argue that the emergence of semantic interoperability can be seen as an economic process among rational agents and, although interoperability can be mutually beneficial for the involved parties, it may also be costly and might fail to emerge. As a sample scenario, we consider the emergence of semantic interoperability among rational web service agents in service-oriented architectures (SOAs), and we analyze their individual economic incentives with respect to utility, risk and cost. We model this process as a positive-sum game and study its equilibrium and evolutionary dynamics. According to our analysis, which is also experimentally verified, certain conditions on the communication cost, the cost of technological adaptation, the expected mutual benefit from interoperability, as well as the expected loss from isolation, drive the process