Nikiforos Karamanis

A computer-aided environment for generating multiple-choice test items

This paper describes a novel computer-aided procedure for generating multiple-choice test items from electronic documents. In addition to employing various Natural Language Processing techniques, including shallow parsing, automatic term extraction, sentence transformation and computing of semantic distance, the system makes use of language resources such as corpora and ontologies. It identifies important concepts in the text and generates questions about these concepts as well as multiple-choice distractors, offering the user the option to post-edit the test items by means of a user-friendly interface. In assisting test developers to produce items in a fast and expedient manner without compromising quality, the tool saves both time and production costs.

Computing Locally Coherent Discourses

We present the first algorithm that computes optimal orderings of sentences into a locally coherent discourse. The algorithm runs very efficiently on a variety of coherence measures from the literature. We also show that the discourse ordering problem is NP-complete and cannot be approximated.

Evaluating centering for information ordering using corpora

In this article we discuss several metrics of coherence defined using centering theory and investigate the usefulness of such metrics for information ordering in automatic text generation. We estimate empirically which is the most promising metric and how useful this metric is using a general methodology applied on several corpora. Our main result is that the simplest metric (which relies exclusively on NOCB transitions) sets a robust baseline that cannot be outperformed by other metrics which make use of additional centering-based features. This baseline can be used for the development of both text-to-text and concept-to-text generation systems.

Natural Language Processing in aid of FlyBase curators

BackgroundDespite increasing interest in applying Natural Language Processing (NLP) to biomedical text, whether this technology can facilitate tasks such as database curation remains unclear.ResultsPaperBrowser is the first NLP-powered interface that was developed under a user-centered approach to improve the way in which FlyBase curators navigate an article. In this paper, we first discuss how observing curators at work informed the design and evaluation of PaperBrowser. Then, we present how we appraise PaperBrowsers navigational functionalities in a user-based study using a text highlighting task and evaluation criteria of Human-Computer Interaction. Our results show that PaperBrowser reduces the amount of interactions between two highlighting events and therefore improves navigational efficiency by about 58% compared to the navigational mechanism that was previously available to the curators. Moreover, PaperBrowser is shown to provide curators with enhanced navigational utility by over 74% irrespective of the different ways in which they highlight text in the article.ConclusionWe show that state-of-the-art performance in certain NLP tasks such as Named Entity Recognition and Anaphora Resolution can be combined with the navigational functionalities of PaperBrowser to support curation quite successfully.

Evaluating Centering-Based Metrics of Coherence

We use a reliably annotated corpus to compare metrics of coherence based on Centering Theory with respect to their potential usefulness for text structuring in natural language generation. Previous corpus-based evaluations of the coherence of text according to Centering did not compare the coherence of the chosen text structure with that of the possible alternatives. A corpus-based methodology is presented which distinguishes between Centering-based metrics taking these alternatives into account, and represents therefore a more appropriate way to evaluate Centering from a text structuring perspective.

Generating Multiple-Choice Test Items from Medical Text: A Pilot Study

We report the results of a pilot study on generating Multiple-Choice Test Items from medical text and discuss the main tasks involved in this process and how our system was evaluated by domain experts.

Evaluating Centering for Sentence Ordering in Two New Domains

This paper builds on recent research investigating sentence ordering in text production by evaluating the Centering-based metrics of coherence employed by Karamanis et al. (2004) using the data of Barzilay and Lapata (2005). This is the first time that Centering is evaluated empirically as a sentence ordering constraint in several domains, verifying the results reported in Karamanis et al.

A Corpus-Based Methodology for Evaluating Metrics of Coherence for Text Structuring

This paper presents a novel corpus-based methodology for comparing metrics of coherence with respect to their potential usefulness for text structuring. Different definitions of such metrics, all using notions from Centering Theory, are discussed, and the methodology is applied to existing data derived from the MPIRO generation system.

Text Mining for Biology and Biomedicine Sophia Ananiadou and John McNaught (editors) (University of Manchester and UK National Centre for Text Mining) Boston and London: Artech House, 2006, xi+286 pp; hardbound, ISBN 1-58053-984-X, £53.00

A battery separator material which is folded to form an envelope is heat sealed along at least two opposing edges thereof to form a battery separator. The separator material is comprised of discrete polyolefin pulp fibers in a sufficient amount to heat seal the separator along its edges. The fibers are bound by an organic polymeric binder. A process of forming the battery separator is also disclosed.