Computing with meaning by operationalising socio-cognitive semantics

Abstract

This thesis is motivated by the desire to provide technological solutions to enhance human

awareness in information processing tasks. The need is pressing. Paradoxically, as information

piles up people become less and less aware due to perceived scarce cognitive resources.

As a consequence, specialisations become ever more specialised, projects and individuals in

organisations become ever more insular. Technology can enhance awareness by informing

the individual about what is happening outside their speciality. Systems which can assist

people in these ways need to make sense of human communication. The computer system

must know about what it is that it is processing; it must follow a socio-cognitive framework

and reason with it. It must compute with meanings not symbolic surface structures.

The hypothesis of the thesis is that knowledge potentially useful for enhancing awareness

can be derived from interactions between people using computational models based on

socio-cognitive semantics. The goals are whether an appreciable approximation of conceptual

spaces can be realised through semantic spaces, and whether such semantic spaces can

develop representations of meaning which have the potential to enhance the awareness of

users? The two thesis questions are how well the socio-cognitive framework of G¨ardenfors

could be brought into operational reality, and if a bridge can be made, then what practical

issues can be involved?

The theory of conceptual spaces of Peter G¨ardenfors is combined with methods from

cognitive science for creating geometric spaces to represent meaning. Hyperspace Analogue

to Language and Latent Semantic Analysis are used as exemplars of the cognitive science

algorithms. The algorithms are modified by a variety of syntactic processing schemes to

overcome a paucity of data and hence lack of expressivity in representations of meaning:

part-of-speech tagging, index expressions and anaphora resolution are effected and incorporated

into the semantic space.

The practical element of the thesis consists of five case studies. These are developed in

two parts: studies describing how meaning changes and evolves in semantic spaces, and studies

describing semantic space applications featuring knowledge discovery. These studies are

in a variety of domains with a variety of data: online communities of interest using a mailing

list, a health-based mailing list, organisational blogs, "hallway chatter", and organisational

email. The data is real world utterances that provide the situational factors that cognitive

systems need to answer queries and provide context. The amounts of data are significantly less than previously used by semantic space methods, hence the need for syntactic assistance.

The particular problems examined in the case studies are corporate expertise management,

social network discovery, tracking ebbs and flows of topics, and noticing the change in a

person's sense-of-self over time. These are significantly different to those usually examined

using semantic spaces.

The key differentiator of this work stems from its focus on the geometrically-based computational

realisation of meaning. This thesis takes semantic spaces out of the closet and into

real-world information technology applications, with a roadtest in real life.