George Demetriou

Two applications of information extraction to biological science journal articles: enzyme interactions and protein structures.

Information extraction technology, as defined and developed through the U.S. DARPA Message Understanding Conferences (MUCs), has proved successful at extracting information primarily from newswire texts and primarily in domains concerned with human activity. In this paper we consider the application of this technology to the extraction of information from scientific journal papers in the area of molecular biology. In particular, we describe how an information extraction system designed to participate in the MUC exercises has been modified for two bioinformatics applications: EMPathIE, concerned with enzyme and metabolic pathways; and PASTA, concerned with protein structure. Progress to date provides convincing grounds for believing that IE techniques will deliver novel and effective ways for scientists to make use of the core literature which defines their disciplines.

Protein Structures and Information Extraction from Biological Texts: The PASTA System

MOTIVATION The rapid increase in volume of protein structure literature means useful information may be hidden or lost in the published literature and the process of finding relevant material, sometimes the rate-determining factor in new research, may be arduous and slow. RESULTS We describe the Protein Active Site Template Acquisition (PASTA) system, which addresses these problems by performing automatic extraction of information relating to the roles of specific amino acid residues in protein molecules from online scientific articles and abstracts. Both the terminology recognition and extraction capabilities of the system have been extensively evaluated against manually annotated data and the results compare favourably with state-of-the-art results obtained in less challenging domains. PASTA is the first information extraction (IE) system developed for the protein structure domain and one of the most thoroughly evaluated IE system operating on biological scientific text to date. AVAILABILITY PASTA makes its extraction results available via a browser-based front end: http://www.dcs.shef.ac.uk/nlp/pasta/. The evaluation resources (manually annotated corpora) are also available through the website: http://www.dcs.shef.ac.uk/nlp/pasta/results.html.

Building a semantically annotated corpus of clinical texts

In this paper, we describe the construction of a semantically annotated corpus of clinical texts for use in the development and evaluation of systems for automatically extracting clinically significant information from the textual component of patient records. The paper details the sampling of textual material from a collection of 20,000 cancer patient records, the development of a semantic annotation scheme, the annotation methodology, the distribution of annotations in the final corpus, and the use of the corpus for development of an adaptive information extraction system. The resulting corpus is the most richly semantically annotated resource for clinical text processing built to date, whose value has been demonstrated through its use in developing an effective information extraction system. The detailed presentation of our corpus construction and annotation methodology will be of value to others seeking to build high-quality semantically annotated corpora in biomedical domains.

Observing users, designing clarity: a case study on the user-centered design of a cross-language information retrieval system

This report presents a case study of the development of an interface for a novel and complex form of document retrieval: searching for texts written in foreign languages based on native language queries. Although the underlying technology for achieving such a search is relatively well understood, the appropriate interface design is not. A study involving users from the beginning of the design process is described, and it covers initial examination of user needs and tasks, preliminary design and testing of interface components, building, testing, and refining the interface, and, finally, conducting usability tests of the system. Lessons are learned at every stage of the process, leading to a much more informed view of how such an interface should be built.

Bioinformatics applications of information extraction from scientific journal articles

Information extraction technology, as defined and developed through the US Defense Advanced Research Projects Agency (DARPA) Message Understanding Conferences (MUCs), has proved successful at extracting information primarily from newswire texts and primarily in domains concerned with human activity. In this paper, the application of this technology to the extraction of information from scientific journal papers in the area of molecular biology is considered. In particular, it is described how an information extraction designed to participate in the MUC exercises has been modified for two bioinformatics applications: one concerned with enzyme and metabolic pathways; the other with protein structure. Progress to date provides convincing grounds for believing that information extraction techniques will deliver novel and effective ways for scientists to make use of the core literature which defines their disciplines.

Exploring the Effect of Query Translation when Searching Cross-Language

A usability study of Clarity, a cross language information retrieval system for rare languages, is presented. Clarity aims at investigating CLIR for so-called low-density languages, those with few translation resources. The usability study explored two different levels of feedback and control over the query translation mechanism. Techniques like word-by-word translation of title and keywords were also tested. Although it would appear that a greater control over query translation enables users to retrieve more relevant documents a great difference among participants, topics, and tasks was discovered. Indeed the user engagement with the searching task is extremely subjective and variable, thus affecting the homogeneity of the results and preventing any statistical validity. A revision of the current evaluation schema is important to get a better understanding of user-CLIR interaction and some issues on different ways of measuring user’s performance are outlined in this perspective.

Web Service Architectures for Text Mining: An Exploration of the Issues via an E-Science Demonstrator

Text mining technology can be used to assist in finding relevant or novel information in large volumes of unstructured data, such as that which is increasingly available in the electronic scientific literature. However, publishers are not text mining specialists, nor typically are the end user scientists who consume their products. This situation suggests a web services based solution, where text mining specialists process the literature obtained from publishers and make their results available to remote consumers (research scientists). In this paper we discuss the integration of web services and text mining within the domain of scientific publishing and explore the strengths and weaknesses of three generic architectural designs for delivering text mining web services. We argue for the superiority of one of these and demonstrate its viability by reference to an application designed to provide access to the results of text mining over the PubMed database of scientific abstracts.