Tristan Miller

EFFICIENT DEFEASIBLE REASONING SYSTEMS

For many years, the non-montonic reasoning community has focussed on highly expressive logics. Such logics have turned out to be computationally expensive, and have given little support to the practical use of non-monotonic reasoning. In this work we discuss defeasible logic, a less-expressive but more efficient non-monotonic logic. We report on two new implemented systems for defeasible logic: a query answering system employing a backward-chaining approach, and a forward-chaining implementation that computes all conclusions. Our experimental evaluation demonstrates that the systems can deal with large theories (up to hundreds of thousands of rules). We show that defeasible logic has linear complexity, which contrasts markedly with most other non-monotonic logics and helps to explain the impressive experimental results. We believe that defeasible logic, with its efficiency and simplicity, is a good candidate to be used as a modeling language for practical applications, including modelling of regulations and business rules.

Essay Assessment with Latent Semantic Analysis

Latent semantic analysis (LSA) is an automated, statistical technique for comparing the semantic similarity of words or documents. In this article, I examine the application of LSA to automated essay scoring. I compare LSA methods to earlier statistical methods for assessing essay quality, and critically review contemporary essay-scoring systems built on LSA, including the Intelligent Essay Assessor, Summary Street, State the Essence, Apex, and Select-a-Kibitzer. Finally, I discuss current avenues of research, including LSAs application to computer-measured readability assessment and to automatic summarization of student essays.

Efficient defeasible reasoning systems

For many years, the non-monotonic reasoning community has focussed on highly expressive logics. Such logics have turned out to be computationally expensive, and have given little support to the practical use of non-monotonic reasoning. In this work we discuss defeasible logic, a less-expressive but more efficient non-monotonic logic. We report on two new implemented systems for defeasible logic: a query answering system employing a backward chaining approach, and a forward-chaining implementation that computes all conclusions. Our experimental evaluation demonstrates that the systems can deal with large theories (up to hundreds of thousands of rules). We show that defeasible logic has linear complexity, which contrasts markedly with most other non-monotonic logics and helps to explain the impressive experimental results. We believe that defeasible logic, with its efficiency and simplicity is a good candidate to be used as a modelling language for practical applications, including modelling of regulations and business rules.

Attention-based information retrieval using eye tracker data

We describe an automated keyword extraction system which uses an eye tracker to identify those areas of a written document the reader finds of greatest interest. The keywords thus extracted are then used in the back end of an information retrieval system to help the user find other documents which contain information of interest to him.

Word Completion with Latent Semantic Analysis

Current word completion tools rely mostly on statistical or syntactic knowledge. Can using semantic knowledge improve the completion task? We propose a language-independent word completion algorithm which uses latent semantic analysis (LSA) to model the semantic context of the word being typed. We find that a system using this algorithm alone achieves keystroke savings of 56% and a hit rate of 42%. This represents improvements of 6.9% and 17%, respectively, over existing approaches

On the use of topic models for word completion

We investigate the use of topic models, such as probabilistic latent semantic analysis (PLSA) and latent Dirichlet allocation (LDA), for word completion tasks. The advantage of using these models for such an application is twofold. On the one hand, they allow us to exploit semantic or contextual information when predicting candidate words for completion. On the other hand, these probabilistic models have been found to outperform classical latent semantic analysis (LSA) for modeling text documents. We describe a word completion algorithm that takes into account the semantic context of the word being typed. We also present evaluation metrics to compare different models being used in our study. Our experiments validate our hypothesis of using probabilistic models for semantic analysis of text documents and their application in word completion tasks.

Security issues for pervasive personalized communication systems

Technological progress allows us to equip any mobile phone with new functionalities, such as storing personalized information about its owner and using the corresponding personal profile for enabling communication to persons whose mobile phones represent similar profiles. However, this raises very specific security issues, in particular relating to the use of Bluetooth technology. Herein we consider such scenarios and related problems in privacy and security matters. We analyze in which respect certain design approaches may fail or succeed at solving these problems. We concentrate on methods for designing the user-related part of the communication service appropriately in order to enhance confidentiality.

Why I Will Never Have a Girlfriend

Informal empirical and anecdotal evidence from the (male) scientific community has long pointed to the difficulty in securing decent, long-term female companionship. To date, however, no one has published a rigorous study of the matter. In this essay, the author investigates himself as a case study and presents a proof, using simple statistical calculus, of why it is impossible to find a girlfriend. Why don’t I have a girlfriend? This is a question that practically every male has asked himself at one point or another in his life. Unfortunately, there is rarely a hard and fast answer to the query. Many men try to reason their way through the dilemma nonetheless, often reaching a series of ridiculous explanations, each more self-deprecating than the last: “Is it because I’m too shy, and not aggressive enough? Is it my opening lines? Am I a boring person? Am I too fat or too thin? Or am I simply ugly and completely unattractive to women?” When all other plausible explanations have been discounted, most fall back on the time-honoured conclusion that “there must be Something WrongTM with me” before resigning themselves to lives of perpetual chastity.1 ∗This paper was written when the author was at Griffith University, Australia. After a short period of brooding, of course, these males will eventually come to the realization that the real reason they were never able to get a girlfriend is Not the author, though. I, for one, refuse to spend my life brooding over my lack of luck with women. While I’ll be the first to admit that my chances of ever entering into a meaningful relationship with someone special are practically non-existent, I staunchly refuse to admit that it has anything to do with some inherent problem with me. Instead, I am convinced that the situation can be readily explained in purely scientific terms, using nothing more than demographics and some elementary statistical calculus. Lest anyone suspect that my standards for women are too high, let me allay those fears by enumerating in advance my three criteria for the match. First, the potential girlfriend must be approximately my age—let’s say 21 plus or minus three or four years. Second, the girl must be beautiful (and I use that term allencompassingly to refer to both inner and outer beauty). Third, she must also be reasonably intelligent—she doesn’t have to be Mensa material, but the ability to carry on a witty, insightful argument would be nice. So there they are—three simple demands, which I’m sure everyone will agree are anything but unreasonable. That said, I now present my demonstration of why the probability of finding a suitthat they were too discriminating with their attentions. They will consequently return to the dating scene, entering a sequence of blase relationships with mediocre girls for whom they don’t really care, until they finally marry one out of fear of spending the rest of their lives alone. I am convinced that this behaviour is the real reason for today’s alarmingly high divorce rate.