Human-centered Knowledge Research Articles

ECONOMIC KNOWLEDGE IN ISLAMIC ECONOMIC DOCTRINE IS A PHILOSOPHICAL VISION

The separatism that represents the challenge existing between reason and revelation is a distinctive feature of the Western intellectual heritage. This separatism arose from the concept of conceptualizing existential convergence, which enables philosophers to use standards of judgment to measure the outcomes of both reason and revelation. This existential convergence leads to the equality of fields. Cognitivism, and subjecting judgments to criteria or standards like this is in fact a declaration of the true sovereignty of reason, which led to man becoming the focus of Western philosophy, the dialectic of (Locke) that most knowledge comes from experience, and the hypothesis of (Kent) that knowledge A joint product of the mind and the external world, and the certainty of (Auguste Comte) which focuses on the scientific stage as opposed to the metaphysical and theological stages, and the experimental radicalism of (William James) are all many ideas stemming from the cognitive foundations presented by Aristotle’s empirical doctrine and keeping pace with human-centered knowledge. The approximation of the levels of existentialism stemming from the syncretic atmosphere of the Roman era, which was an essential element in Christianity, was gradually subjected to the two systems. Hume’s interpretation of God as the spirit of the material world, Hobbesian materialism in metaphysics, the theory of thought (the Absolute, the specific deity), and James’s idea of finiteness. Thinking are all exciting stages of formulating the cognitively specific existential theory of the Western heritage, which established a new model (Ihsanoglu, 2000, 122).

PU-GEN: Enhancing generative commonsense reasoning for language models with human-centered knowledge

Generative commonsense reasoning refers to the ability of a language model to generate a sentence with a given concept-set based on compositional generalization and commonsense reasoning. In the CommonGen challenge, which evaluates the capability of generative commonsense reasoning, language models continue to exhibit low performances and struggle to leverage knowledge representation from humans. Therefore, we propose PU-GEN to leverage human-centered knowledge in language models to enhance compositional generalization and commonsense reasoning considering the human language generation process. To incorporate human-centered knowledge, PU-GEN reinterprets two linguistic philosophies from Wittgenstein: picture theory and use theory. First, we retrieve scene knowledge to reflect picture theory such that a model can describe a general situation as if it were being painted. Second, we extend relational knowledge to consider use theory for understanding various contexts. PU-GEN demonstrates superior performance in qualitative and quantitative evaluations over baseline models in CommonGen and generates convincing evidence for CommonsenseQA. Moreover, it outperforms the state-of-the-art model used in the previous CommonGen challenge.

An interactive human centered data science approach towards crime pattern analysis

The traditional machine learning systems lack a pathway for a human to integrate their domain knowledge into the underlying machine learning algorithms. The utilization of such systems, for domains where decisions can have serious consequences (e.g. medical decision-making and crime analysis), requires the incorporation of human experts' domain knowledge. The challenge, however, is how to effectively incorporate domain expert knowledge with machine learning algorithms to develop effective models for better decision making.In crime analysis, the key challenge is to identify plausible linkages in unstructured crime reports for the hypothesis formulation. Crime analysts painstakingly perform time-consuming searches of many different structured and unstructured databases to collate these associations without any proper visualization. To tackle these challenges and aiming towards facilitating the crime analysis, in this paper, we examine unstructured crime reports through text mining to extract plausible associations. Specifically, we present associative questioning based searching model to elicit multi-level associations among crime entities. We coupled this model with partition clustering to develop an interactive, human-assisted knowledge discovery and data mining scheme.The proposed human-centered knowledge discovery and data mining scheme for crime text mining is able to extract plausible associations between crimes, identifying crime pattern, grouping similar crimes, eliciting co-offender network and suspect list based on spatial-temporal and behavioral similarity. These similarities are quantified through calculating Cosine, Jacquard, and Euclidean distances. Additionally, each suspect is also ranked by a similarity score in the plausible suspect list. These associations are then visualized through creating a two-dimensional re-configurable crime cluster space along with a bipartite knowledge graph.This proposed scheme also inspects the grand challenge of integrating effective human interaction with the machine learning algorithms through a visualization feedback loop. It allows the analyst to feed his/her domain knowledge including choosing of similarity functions for identifying associations, dynamic feature selection for interactive clustering of crimes and assigning weights to each component of the crime pattern to rank suspects for an unsolved crime.We demonstrate the proposed scheme through a case study using the Anonymized burglary dataset. The scheme is found to facilitate human reasoning and analytic discourse for intelligence analysis.

The Pedagogical Power of Things: Toward a Post-Intentional Phenomenology of Unlearning

The Pedagogical Power of ThingsToward a Post-Intentional Phenomenology of Unlearning Tyson E. Lewis (bio) Jane Bennett's book Vibrant Matter: A Political Ecology of Things has two overlapping and mutually supportive aims. First, she has a philosophical project: to problematize and hopefully overcome a major bias in Western philosophical thinking that separates life and death, activity and passivity, vibrancy and inertness. As counterintuitive as it may seem, Bennett proposes that brute matter exerts its own power that exists below the human world. Focusing on the "vitality" of things means coming to terms with the "capacity of things … not only to impede or block the will and designs of humans but also to act as quasi agents or forces with trajectories, propensities, or tendencies of their own" (viii). This philosophical project is linked directly to an overarching political hypothesis. Bennett argues that one of the causes of the destruction of the natural world and the impending ecological disaster is precisely the Western belief that matter is inactive, a mere resource for human consumption. But, if we see matter as vibrant and powerful then perhaps we will not instrumentalize it or uncritically consume it. Here I do not want to review possible criticisms of these two projects or their underlying assumptions and arguments. Instead I want to bracket off these lines of inquiry in order to expose and think through another project of this book, one which Bennett only indirectly gestures toward but is nevertheless essential for forming a bridge between the philosophical and political poles of her overall aim. This other project concerns the possibility of an aesthetic pedagogy of things—a new educational practice that would route our collective attention away from issues of cultivating human-centered knowledge, skills, and aptitudes toward a perceptual receptivity and attentiveness to things that fall outside our worldly concerns. I call this an "aesthetic pedagogy" first [End Page 122] and foremost because it concerns the sensorial dimension of our experience of things—their ability to gross us out, make us feel uncanny, or provoke weird pleasures that emerge when we recognize the secrete lives of things. Although much more focused on philosophical and political issues, varieties of speculative realism (including object-oriented, vitalist, and materialist incarnations) do have a weak strain running through them that concerns educational questions. Like Bennett, Ian Bogost ends his book Alien Phenomenology, or What It Is Like to Be a Thing with a gesture toward the meaning and purposes of education. Critical of STEAM (science, technology, engineering, art, and mathematics) educational policies, Bogost observes that when all art and science are reduced to instrumental ends serving predefined economic functions, then there is no room left in education for the experience of things as such. He writes, "But what if the real obstacle to youthful interest in science arises not from a distaste for mathematics or the natural world but from a latent dissatisfaction with the way science melts the shell of wonder around ordinary objects?" (129). Bogost, like Bennett, sees things as an interruption of anthropocentric (human-centered) educational aims, opening up a space wherein the mere thingliness of the thing can appear in its own right. The goal here is not to reduce things to resources that can be studied in order to improve human worlds. Rather it is to let shine the irreducible material power of things. Of course, such thingly presence can be important for rethinking future political actions, but such actions need to be predicated on a perceptual sensitivity toward the weirdness of things as such. For both Bennett and Bogost, an aesthetic education in things is essential, yet largely undertheorized. In the rest of this article, I will tease out the complexity of such an education. What is at stake here is an education that does not merely reinforce the human-centered nature of perceptual grasping but rather reveals something about perception itself that is object-centered (or, even better, object-infused). In this sense, things need to be seen as having pedagogical power of their own, as nonhuman teachers that do work on our perceptual common-sense orientations and bodily comportments. Instead of human perception shaping how things appear, I want...

The Scope of Design Knowledge: Integrating the Technically Rational and Human-Centered Dimensions

This paper examines design from a ‘knowledge integration’ research perspective, a field which enables us to explore the nature and scope of the knowledge involved in design. The integration of technically rational and human-centered knowledge is central to design (‘integration of design’). However, design is also a core knowledge generating process (‘integration by design’) which, although sometimes overlooked, elevates design from a functional task to a strategic activity of the firm. The paper explores the meaning and implications of the scope of design knowledge, highlighting the interplay between technically rational and human-centered aspects, including symbolism, meaning and aesthetics. By examining how the nature and scope of the design knowledge being integrated influences the design process we deepen our understanding of the complexities of design and design practice.

Experience-based support for human-centered knowledge modeling

The construction, capture and sharing of human knowledge is one of the fundamental problems of human-centered computing. Electronic concept maps have proven to be a useful vehicle for building knowledge models. However, the user has to deal with the difficult task of deciding what information to include in these models. This article reports the culmination of a multi-year research project aimed at developing intelligent suggesters designed to aid users of concept mapping tools as they build their knowledge models. It describes Discerner and Extender, two proactive suggesters that can be incorporated into the CmapTools concepts mapping system. Discerner applies case-based reasoning techniques to suggest potentially useful propositions mined from other users’ knowledge models, while Extender mines search engines to suggest new related areas to model. The article presents experimental results addressing two previously open questions for the project: Discerner’s retrieval accuracy and Extender’s ability to generate artificial topics with content similar to topics determined by domain experts. Both experiments show satisfactory results.

Knowledge sharing in dynamic virtual enterprises: A socio-technological perspective

The success of a virtual enterprise depends largely on the effective collaboration of its members in orchestrating their knowledge, skills, core competences and resources, in order to enhance competitive capabilities and respond better to business opportunities. In this paper we address the challenges of knowledge sharing in dynamic virtual enterprises. We take a socio-technological approach by proposing a human-centered knowledge sharing solution and architecture. Specifically, we propose a knowledge resource space model to represent heterogeneous knowledge resources, both explicit and implicit. We then introduce a knowledge sharing community model and adopt an agent based solution to perform the functions of knowledge sharing among members of a dynamic virtual enterprise. Our solution incorporates the concepts of agent society and semantic ontology. Knowledge sharing in dynamic virtual enterprises is performed with three types of ties: knowledge agent to knowledge agent, knowledge agent to knowledge item, and knowledge item to knowledge item. We measure agent-to-agent ties by preference correlation using the contribution degree of one agent to another and the preference similarity degree between two agents. We define a semantic view to show agent-to-item ties and use semantic links in the knowledge resource space model to reflect item-to-item ties. We also elaborate the co-evolution mechanism of collective intelligence across enterprises throughout the lifecycle of a dynamic virtual enterprise. A case study is presented to validate our approach.

The Importance of Process Thinking in Business Intelligence

The growing field of Operational Business Intelligence (BI) has resulted in increasing interest in BI-supported Business Processes (BPs), including their management and ongoing improvement. This has led BI practitioners to consider another field–Business Process Management (BPM)–that is closely related to business performance management. However, current approaches to the BPM and operational BI integration have been limited and reduced to the problem of technical integration of BPM and BI systems. This paper argues that by adopting process- thinking in BI, further opportunities for business value creation could be discovered through systematic analysis of the non-technical aspects of BI and BPM integration, including strategy alignment, human-centered knowledge management, and ongoing improvement of BI supported processes. The authors propose a theoretical framework founded in the related research in BPM, BI, and Knowledge Management (KM) fields, describing the ways it has been used to guide ongoing empirical research in diverse case organizations across different industry sectors.

Qualitative Analysis of Semantically Enabled Knowledge Management Systems in Agile Software Engineering

In many agile software engineering organizations there is not enough time to follow knowledge management processes, to retrieve knowledge in complex processes, or to systematically elicit knowledge. This chapter gives an overview about the human-centered design of semantically-enabled knowledge management systems based on Wikis used in agile software engineering environments. The methodology – developed in the RISE (Reuse in Software Engineering) project – enables and supports the design of human-centered knowledge sharing platforms, such as Wikis. Furthermore, the paper specifies requirements one should keep in mind when building human-centered systems to support knowledge management. A two-phase qualitative analysis showed that the knowledge management system acts as a flexible and customizable view on the information needed during working-time which strongly relieves software engineers from time-consuming retrieval activities. Furthermore, the observations gave some hints about how the software system supports the collection of vital working experiences and how it could be subsequently formed and refined.

Human-centered knowledge acquisition: a structural learning theory approach

This paper develops the application of structural learning theory (SLT) to support the knowledge engineer (KE) in the knowledge acquisition process and the development of expert systems. The underlying research focuses on the knowledge to elicit from skilled domain problem solvers, and the structure(i.e. form and type) of this knowledge using SLT to guide elicitation and interpretation. SLT explicitly models both declarative and procedural knowledge, while presuming an innate backward-chaining mechanism. Guidelines based on SLT allow knowledge engineers to concentrate on the human-centered knowledge of domain specific problem solvers. In fact, the SLT model presumes that skilled problem solvers do not automatically divulge all rules. This human-centered, needs-based approach provides a point of departure from previous knowledge acquisition methods and serves as a distinguishing feature of this knowledge acquisition method. Specifically grounded in SLT, distinct rule types are developed to be extracted from skilled domain problem solvers. Based on these rule types, guidelines are developed to aid the KEs in the acquisition process.

Operator Support in Traffic Management: A Heuristics Model and Experimental Study

The identification of problems from numeric traffic measurements is an important part of control center activities in ATMS (Advanced Traffic Management Systems). However, an information modeling process that relies solely upon ‘traditional’ quantitative data analysis does not reflect faithfully the actual methods used by human operators. In addition to common-sense knowledge and specific contextual information, operators also use various heuristics and rules-of-thumb to supplement the numerical analysis. This paper describes an experiment to examine the effectiveness of an expert system that integrates quantitative and qualitative traffic information using a human-centered knowledge system design. The system's performance was investigated using a data suite of real traffic scenarios; the statistically significant results showed that the integrated process had superior performance compared to the ‘traditional’ quantitative analysis running alone.