Application of aboutness to functional benchmarking in information retrieval

Experimental approaches are widely employed to benchmark the performance of an information retrieval (IR) system. Measurements in terms of recall and precision are computed as performance indicators. Although they are good at assessing the retrieval effectiveness of an IR system, they fail to explore deeper aspects such as its underlying functionality and explain why the system shows such performance. Recently, inductive (i.e., theoretical) evaluation of IR systems has been proposed to circumvent the controversies of the experimental methods. Several studies have adopted the inductive approach, but they mostly focus on theoretical modeling of IR properties by using some metalogic. In this article, we propose to use inductive evaluation for functional benchmarking of IR models as a complement of the traditional experiment-based performance benchmarking. We define a functional benchmark suite in two stages: the evaluation criteria based on the notion of "aboutness," and the formal evaluation methodology using the criteria. The proposed benchmark has been successfully applied to evaluate various well-known classical and logic-based IR models. The functional benchmarking results allow us to compare and analyze the functionality of the different IR models

The Nature and Implementation of Representation in Biological Systems

I defend a theory of mental representation that satisfies naturalistic constraints. Briefly, we begin by distinguishing (i) what makes something a representation from (ii) given that a thing is a representation, what determines what it represents. Representations are states of biological organisms, so we should expect a unified theoretical framework for explaining both what it is to be a representation as well as what it is to be a heart or a kidney. I follow Millikan in explaining (i) in terms of teleofunction, explicated in terms of natural selection. To explain (ii), we begin by recognizing that representational states do not have content, that is, they are neither true nor false except insofar as they both “point to” or “refer” to something, as well as “say” something regarding whatever it is they are about. To distinguish veridical from false representations, there must be a way for these separate aspects to come apart; hence, we explain (ii) by providing independent theories of what I call f-reference and f-predication (the ‘f’ simply connotes ‘fundamental’, to distinguish these things from their natural language counterparts). Causal theories of representation typically founder on error, or on what Fodor has called the disjunction problem. Resemblance or isomorphism theories typically founder on what I’ve called the non-uniqueness problem, which is that isomorphisms and resemblance are practically unconstrained and so representational content cannot be uniquely determined. These traditional problems provide the motivation for my theory, the structural preservation theory, as follows. F-reference, like reference, is a specific, asymmetric relation, as is causation. F-predication, like predication, is a non-specific relation, as predicates typically apply to many things, just as many relational systems can be isomorphic to any given relational system. Putting these observations together, a promising strategy is to explain f-reference via causal history and f-predication via something like isomorphism between relational systems. This dissertation should be conceptualized as having three parts. After motivating and characterizing the problem in chapter 1, the first part is the negative project, where I review and critique Dretske’s, Fodor’s, and Millikan’s theories in chapters 2-4. Second, I construct my theory about the nature of representation in chapter 5 and defend it from objections in chapter 6. In chapters 7-8, which constitute the third and final part, I address the question of how representation is implemented in biological systems. In chapter 7 I argue that single-cell intracortical recordings taken from awake Macaque monkeys performing a cognitive task provide empirical evidence for structural preservation theory, and in chapter 8 I use the empirical results to illustrate, clarify, and refine the theory

Discovering information flow using a high dimensional conceptual space

This paper presents an informational inference mechanism realized via the use of a high dimensional conceptual space. More specifically, we claim to have operationalized important aspects of G?rdenforss recent three-level cognitive model. The connectionist level is primed with the Hyperspace Analogue to Language (HAL) algorithm which produces vector representations for use at the conceptual level. We show how inference at the symbolic level can be implemented by employing Barwise and Seligmans theory of information flow. This article also features heuristics for enhancing HAL-based representations via the use of quality properties, determining concept inclusion and computing concept composition. The worth of these heuristics in underpinning informational inference are demonstrated via a series of experiments. These experiments, though small in scale, show that informational inference proposed in this article has a very different character to the semantic associations produced by the Minkowski distance metric and concept similarity computed via the cosine coefficient. In short, informational inference generally uncovers concepts that are carried, or, in some cases, implied by another concept, (or combination of concepts)

Content, Mental Representation and Intentionality: Challenging the Revolutionary Character of Radical Enactivism

Criticisms and rejections of representationalism are increasingly popular in 4E cognitive science, and especially in radical enactivism. But by overfocusing our attention on the debate between radical enactivism and classical representationalism, we might miss the woods for the trees, in at least two respects: fi rst, by neglecting the relevance of other theoretical alternatives about representationalism in cognitive science; and second by not seeing how much REC and classical representationalism are in agreement concerning basic and problematic issues dealing with mental content and intentionality. In order to expand and exemplify these ideas, this paper presents two heterodox positions on intentionality and on the relations between content and representation. Special attention is paid to the way REC is rejecting these positions: I argue that this rejection reveals common assumptions with classical representationalism, but also undermines the coherence of REC’s conception of intentionality

Content, Mental Representation and Intentionality: Challenging the Revolutionary Character of Radical Enactivism

Criticisms and rejections of representationalism are increasingly popular in 4E cognitive science, and especially in radical enactivism. But by overfocusing our attention on the debate between radical enactivism and classical representationalism, we might miss the woods for the trees, in at least two respects: fi rst, by neglecting the relevance of other theoretical alternatives about representationalism in cognitive science; and second by not seeing how much REC and classical representationalism are in agreement concerning basic and problematic issues dealing with mental content and intentionality. In order to expand and exemplify these ideas, this paper presents two heterodox positions on intentionality and on the relations between content and representation. Special attention is paid to the way REC is rejecting these positions: I argue that this rejection reveals common assumptions with classical representationalism, but also undermines the coherence of REC’s conception of intentionality