Sulieman Bani-Ahmad . Department of Information Technology, Al-Balqa Applied University. Salt, Jordan. Researcher

A content-driven search-keyword (SK-) Suggester for keyword-based search in digital libraries is proposed. Suggesting search terms while the user is entering search terms is helpful for constructing correctly-typed and focused search terms for digita l library queries. The proposed SK-Suggester is bas ed on pre-analyzing step of the publication collection to be searched. The pre-analysis step consists of the following. (i) We parse the document collection usi ng a Link-Grammar parser, a syntactic parser of English , next, (ii) we group publications based on their research topics, (iii) after that, the parser output is used to build a hierarchical structure of simple an d compound tokens to be used to suggest search term s. In order to sort the suggested terms, we use the Te xtRank algorithm, a text summarization tool, to assi gn topic-sensitive scores to the simple and compound t okens. The identified research topics are used to h elp user entering focused search terms prior to the act ual search query execution. The topic-sensitive TextRank scores are further refined to incorporate t he user’s citation behavior model proposed in [Bani- Ahmad, S., Ozsoyoglu, T. 2009]. We experimentally show that the proposed framework promises a more scalable, high quality, and user- friendly SK-Suggester when compared to its competitors. We validate our proposal experimentally using a subset of the ACM SIGMOD Anthology digital library as a testbed, and by employing the research- pyramid model to identify the research topics.

Jamshed Mistry. Sawyer School of Business. Suffolk University. Tel: 617-

This paper describes a model for providing integrat ive decision-making experiences in the core undergraduate management curriculum through the use of an ERP system. The model uses ERP decision-making modules that are situated in an org anizational process and involve students in hands-o n decision making using an ERP system. We also presen t a prototype Oracle-based budgeting decision- making module for a management accounting course, a nd examine its effectiveness in teaching core concepts. These results provide the foundation for: a) developing Oracle-based exercises throughout th e management curriculum that can be used to facilitat e student understanding of integrated business processes and b) using integrated data for managerial decision making.

Eric Simon . Institut du management de l’information, Université de Neuchâtel, Switzerland. Researcher

In systems life cycle management (SLCM), a gap exists between the informal methodologies for systems development and the mathematical formalisms needed for the automatic validation of systems properties and correctness proofs. This paper presents a model based on finite state machines and its translation into Petri nets, a mathematical representation with the desired degree of provability in this context. We a rgue that the model effectively bridges the gap between the intuitive representation of development process es on one hand, and the formal model necessary for val idation on the other hand, by allowing users withou t scientific or technical background to represent the ir activities and all their key features using simp le automata, by applying a systems thinking approach t o problem solving, instead of having to express the model in a more complicated representation from the start. Also, this model shows very promising results in other domains routinely modelled as activities, using other formalisms, like business processes.

Thierry Le Pors. Naval academy, Naval Academy Research Institute, Lanvéoc Poulmic, BP

This paper focuses on simulating naturalistic decis ion making of experts in complex situations. The cognitive model described here is integrated into a multi-agent system. It integrates theories of Natu ral Decision Making with the purpose of producing reali stic simulated decision. This model uses fuzzy representations for the identification of different elements of a situation, and pattern matching betw een the current situation and a set of typical known si tuations. We propose a conception methodology to build Decision Roles Based on Patterns (DRBP). Then, t o validate this model, we choose to apply it to maritime traffic. Maritime traffic simulation requi res elaborated cognitive features: the collision regulations require interpretation and rely to a ce rtain extent on anticipation of the actions of the other ship.

Dominic Heutelbeck University of Hagen - D-58084 Hagen - Germany.

Distributed space partitioning trees (DPSTs) (Heute lbeck and Hemmje, 2006) describe a distributed spatial index for storage and access of the so-called location knowledge. Location knowledge is acquired in a complex distributed process through positionin g, tracking, and program logic to support location- based services which are based upon knowledge about the physical location, shape, and size of real and virtual entities, such as persons, vehicles, cities or other location-based services. Location knowled ge is needed at diverse applications in geographical info rmation systems (GIS), virtual collaboration system s and mobility management. The previous implementatio n of a DSPT, RectNet (Heutelbeck and Hemmje, 2006), was built on an adaptive binary tree shaped network topology. The use of a recursive space partitioning can be useful for load balancing. Howe ver, previous implementation requires complex operations to restructure the network. These operat ions cause significant bursts in network traffic. I n this paper we present VoroDSPT, a new DSPT implementatio n, by using the geometric structure Voronoi Diagram as a topology that provides both greedy-rou ting for supporting efficient spatial queries and information sharing, providing the base for implementing future efficient heuristics of load balancing.

Ismael M. A. Ávila . CPqD R, D Center in Telecommunications. SP- km, 13089-

In the context of an agent-based modeling that esti mates the acceptance of telecenters by their potent ial users in Brazil, this paper discusses two alternativ e configurations of neighborhood for the creation o f social networks, one based on Moore’s cellular auto maton, and another based on random relations. This discussion is an essential step in the creation of the overall model, a bottom up approach in which th e users (agents) are characterized in terms of their technological innovativeness and are subject to the influence of their social networks; each agent is r andomly assigned with a set of initial features in order to reflect the diversity of behaviors and preferenc es found in a field survey with the target audience . The final model is expected to be an evaluation tool to compare alternative digital inclusion strategies i n terms of effectiveness in attracting new users to t he telecenters, and assessing the policies in terms of their efficacy in the resource allocations and of h ow effective is a given equipment deployment strate gy or premise location. This can help to reallocate resources so as to maximize the results.

Thomas Vincent . Equipe MAIA LORIA UHP NANCY 1 BP 239 54506 Vandoeuvre Lès Nancy

Building individual behaviors to solve collective pr oblems is a major stake whose applications are found in several domains. To do so, Dec-POMDP has b een proposed as a formalism for describing multi-agent problems. However, solving a Dec-POMDP turned out to be a NEXP problem. In this study, we introduced the original concept of social action to get round the inherent complexity of Dec-POMDP and we proposed three decentralized reinf orcement learning algorithms which approximate the optimal policy in Dec-POMDP. This a rticle analyses the results obtained and argues that this new approach seems promising for a utomatic top-down collective behavior computation..

Xiaoguang Ma. Department of Electrical, Computer Engineering. Florida State University.

For the Radio Channel Allocation (RCA) of wireless net works, how to efficiently allocate the limited number of channels to achieve high throughput is a challenging problem. The major difficulty in solvin g the RCA problem is to maximize the throughput of the entire network using the min-max optimization scheme. Usually, it is solved by using various heur istic methods, which are known to be NP-hard and have unknown computational scales. In this paper, w e analyze a typical RCA algorithm for IEEE 802.11 based wireless networks including wireless LANs (WL ANs) and wireless mesh networks, namely, the distributed heuristic algorithm (DHA) [2], by using both analytical and statistical analysis in terms of the computational scale (CS) of the method. The CS of an algorithm is defined as the number of channel reallocation times until the network reaches a conv ergence state. By extensive simulations, we demonstrate that DHA reaches the convergence state in finite steps. The total number of channel reallocations is a log-logistic distribution. Based on all the possible network configurations, we develop a method to estimate the CS. We find that the overall upper limit of the CS for a network is O( I), where I is the number of access points (APs) or mesh router s that are responsible for allocating the available radio channels.

Pedro Isaías

Editorial preface for Volume 4, Issue 3 of the IADIS International Journal on Computer Science and Information Systems (IJCSIS). This issue brings together peer-reviewed original research contributions covering the wide spectrum of Information Systems, Artificial Intelligence, Software Engineering, and Digital Transformation.