Modelos de escaneo de gestión estratégica basados en tendencias heurísticas como cuantificadores intensivos de menor información

SS (Strategic Scanning) is unique, partially subjective, inconsistent, interdisciplinary, vague and multidimensional process. Its description and optimisation suffers from IS (Information Shortage) and heterogeneity. IS eliminates straightforward application of traditional statistical methods. Heterogeneity problems are caused by heterogeneous nature of scanned information structures. Artificial Intelligence has developed some tools to solve such problems. Qualitative reasoning is one of them. It is based on the least information intensive quantifiers i.e. trends. There are four different trends i.e. qualitative values and their derivatives: plus/increasing; zero/constant; negative/decreasing; any value / any trend. The paper studies SS models based on ELEs (Equationless Heuristics). An example of ELE is ¿ If novelity is increasing then confidence is decreasing. A solution of a qualitative model is represented by a set S of scenarios and a set T of time transitions among these scenarios. The key information input into an ELE model is subjective knowledge of experts. A consensus among SS experts is often not reached because of inconsistencies of experts¿ knowledge. The SS case study is 12 dimensional (e.g. Freshness, Relevance) and based on 12 ELEs. There are 29 scenariosSS (Strategic Scanning) es un proceso único, parcialmente subjetivo, inconsistente, interdisciplinario, vago y multidimensional. Su descripción y optimización adolece de IS (escasez de información) y heterogeneidad. IS elimina la aplicación directa de los métodos estadísticos tradicionales. Los problemas de heterogeneidad son causados por la naturaleza heterogénea de las estructuras de información escaneadas. La Inteligencia Artificial ha desarrollado algunas herramientas para resolver tales problemas. El razonamiento cualitativo es uno de ellos. Se basa en los cuantificadores que requieren menos información, es decir, las tendencias. Hay cuatro tendencias diferentes, es decir, valores cualitativos y sus derivados: más / creciente; cero / constante; negativo / decreciente; cualquier valor / cualquier tendencia. El artículo estudia los modelos SS basados en ELE (heurística sin ecuaciones). Un ejemplo de ELE es: si la novedad aumenta, la confianza disminuye. La solución de un modelo cualitativo está representada por un conjunto S de escenarios y un conjunto T de transiciones de tiempo entre estos escenarios. La entrada de información clave en un modelo ELE es el conocimiento subjetivo de los expertos. A menudo no se llega a un consenso entre los expertos en SS debido a inconsistencias en el conocimiento de los expertos. El estudio de caso de SS es de 12 dimensiones (por ejemplo, Frescura, Relevancia) y se basa en 12 ELE. Hay 29 escenarios.Universidad Pablo de Olavid

Supporting decision making process with "Ideal" software agents: what do business executives want?

According to Simon’s (1977) decision making theory, intelligence is the first and most important phase in the decision making process. With the escalation of information resources available to business executives, it is becoming imperative to explore the potential and challenges of using agent-based systems to support the intelligence phase of decision-making. This research examines UK executives’ perceptions of using agent-based support systems and the criteria for design and development of their “ideal” intelligent software agents. The study adopted an inductive approach using focus groups to generate a preliminary set of design criteria of “ideal” agents. It then followed a deductive approach using semi-structured interviews to validate and enhance the criteria. This qualitative research has generated unique insights into executives’ perceptions of the design and use of agent-based support systems. The systematic content analysis of qualitative data led to the proposal and validation of design criteria at three levels. The findings revealed the most desirable criteria for agent based support systems from the end users’ point view. The design criteria can be used not only to guide intelligent agent system design but also system evaluation

Abstract A rough-fuzzy document grading system for customized text information retrieval

Due to the large repository of documents available on the web, users are usually inundated by a large volume of information, most of which is found to be irrelevant. Since user perspectives vary, a client-side text filtering system that learns the user's perspective can reduce the problem of irrelevant retrieval. In this paper, we have provided the design of a customized text information filtering system which learns user preferences and modifies the initial query to fetch better documents. It uses a rough-fuzzy reasoning scheme. The rough-set based reasoning takes care of natural language nuances, like synonym handling, very elegantly. The fuzzy decider provides qualitative grading to the documents for the user's perusal. We have provided the detailed design of the various modules and some results related to the performance analysis of the system. Keywords: Text information retrieval; Rough-set based reasoning; Fuzzy membership; Document relevance computation; User preference learnin

Revitalising executive information systems for supporting executive intelligence activities

A thesis submitted for the degree of Doctor of Philosophy of the Univeristy of BedfordshireWith the increasing amount, complexity and dynamism of operational and strategic information in electronic and distributed environment, executives are seeking assistance for continuous, self-reactive and self-adaptive activities or approaches of acquiring, synthesising and interpreting information for intelligence with a view to determining the course of action - executive intelligence activities. Executives Information Systems (EIS) were originally emerged as a computer-based tool to help senior executives to manage the search and process of information. EIS was popularised in 1990's but EIS study have not advanced to a great extent in either research or practice since its prevalence in the mid and late 1990's. Conventional EIS studies have established some views and guidelines for EIS design and development, but the guidelines underpinned by preceding research have failed to develop robust yet rational EIS for handling the current executive's information environment. The most common deficiency of traditional EIS is the static and inflexible function with predetermined information needs and processes designed for static performance monitoring and control. The current emergence of the intelligent software agent, as a concept and a technology, with applications, provides prospects and advanced solutions for supporting executive's information processing activities in a more integrated and distributed environment of the Internet. Although software agents offer the prospective to support information processing activities intelligently, executive's desires and perception of agent-based support must be elucidated in order to develop a system that is considered valuable for executives. This research attempts to identify executive criteria of an agent-based EIS for supporting executive intelligence activities. Firstly, four focus groups were conducted to explore and reveal the current state of executive's information environment and information processing behaviour in the light of Internet era, from which to examine the validity of the conventional views of EIS purpose, functions and design guidelines. Initial executive criteria for agent-based EIS design were also identified in the focus group study. Secondly, 25 senior managers were interviewed for deeper insights on value-added attributes and processes of executive criteria for building agent-based EIS. The findings suggest a "usability-adaptability-intelligence" trichotomy of agent-based EIS design model that comprises executive criteria of value-added attributes and processes for building a usable, adaptable and intelligent EIS