Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems

Lexical Similarities and Differences in the Mathematics, Science and English Language Textbooks

The teaching of Science and Math in English in Malaysia is an area of great concern to educators and students alike. This study looks, in particular, at the common word classes among keywords identified in the Science, Math and English language Form One textbooks used in Malaysia and the differences in language use identified in the Science and Math textbooks

Neurocognitive Informatics Manifesto.

Informatics studies all aspects of the structure of natural and artificial information systems. Theoretical and abstract approaches to information have made great advances, but human information processing is still unmatched in many areas, including information management, representation and understanding. Neurocognitive informatics is a new, emerging field that should help to improve the matching of artificial and natural systems, and inspire better computational algorithms to solve problems that are still beyond the reach of machines. In this position paper examples of neurocognitive inspirations and promising directions in this area are given

Students' difficulties with vector calculus in electrodynamics

Understanding Maxwell's equations in differential form is of great importance when studying the electrodynamic phenomena discussed in advanced electromagnetism courses. It is therefore necessary that students master the use of vector calculus in physical situations. In this light we investigated the difficulties second year students at KU Leuven encounter with the divergence and curl of a vector field in mathematical and physical contexts. We have found that they are quite skilled at doing calculations, but struggle with interpreting graphical representations of vector fields and applying vector calculus to physical situations. We have found strong indications that traditional instruction is not sufficient for our students to fully understand the meaning and power of Maxwell's equations in electrodynamics.Comment: 14 pages, 11 figure

Conceptual and socio-cognitive support for collaborative learning in videoconferencing environments

Studies have shown that videoconferences are an effective medium for facilitating communication between parties who are separated by distance. Furthermore, studies reveal that videoconferences are effective when used for distance learning, particularly when learners are engaged in complex collaborative learning tasks. However, as in face-to-face communication, learners benefit most when they receive additional support for such learning tasks. This article provides an overview of three empirical studies to illustrate more general insights regarding some of the more and less effective ways of supporting collaborative learning with videoconferencing. The focus is on conceptual support, such as structural visualization and socio-cognitive support, such as scripts. Based on the results of the three studies, conclusions can be drawn about the conceptual and socio-cognitive support measures that promote learning. Conclusions can also be reached about the need for employing both conceptual and socio-cognitive support to provide learners with the most benefit

Assessing the quality of a student-generated question repository

We present results from a study that categorizes and assesses the quality of questions and explanations authored by students, in question repositories produced as part of the summative assessment in introductory physics courses over the past two years. Mapping question quality onto the levels in the cognitive domain of Bloom's taxonomy, we find that students produce questions of high quality. More than three-quarters of questions fall into categories beyond simple recall, in contrast to similar studies of student-authored content in different subject domains. Similarly, the quality of student-authored explanations for questions was also high, with approximately 60% of all explanations classified as being of high or outstanding quality. Overall, 75% of questions met combined quality criteria, which we hypothesize is due in part to the in-class scaffolding activities that we provided for students ahead of requiring them to author questions.Comment: 24 pages, 5 figure

Context and Keyword Extraction in Plain Text Using a Graph Representation

Document indexation is an essential task achieved by archivists or automatic indexing tools. To retrieve relevant documents to a query, keywords describing this document have to be carefully chosen. Archivists have to find out the right topic of a document before starting to extract the keywords. For an archivist indexing specialized documents, experience plays an important role. But indexing documents on different topics is much harder. This article proposes an innovative method for an indexing support system. This system takes as input an ontology and a plain text document and provides as output contextualized keywords of the document. The method has been evaluated by exploiting Wikipedia's category links as a termino-ontological resources

From Frequency to Meaning: Vector Space Models of Semantics

Computers understand very little of the meaning of human language. This profoundly limits our ability to give instructions to computers, the ability of computers to explain their actions to us, and the ability of computers to analyse and process text. Vector space models (VSMs) of semantics are beginning to address these limits. This paper surveys the use of VSMs for semantic processing of text. We organize the literature on VSMs according to the structure of the matrix in a VSM. There are currently three broad classes of VSMs, based on term-document, word-context, and pair-pattern matrices, yielding three classes of applications. We survey a broad range of applications in these three categories and we take a detailed look at a specific open source project in each category. Our goal in this survey is to show the breadth of applications of VSMs for semantics, to provide a new perspective on VSMs for those who are already familiar with the area, and to provide pointers into the literature for those who are less familiar with the field