Karen E. Lochbaum

Information Retrieval using a Singular Value Decomposition Model of Latent Semantic Structure

In a new method for automatic indexing and retrieval, implicit higher-order structure in the association of terms with documents is modeled to improve estimates of term-document association, and therefore the detection of relevant documents on the basis of terms found in queries. Singular-value decomposition is used to decompose a large term by document matrix into 50 to 150 orthogonal factors from which the original matrix can be approximated by linear combination; both documents and terms are represented as vectors in a 50- to 150- dimensional space. Queries are represented as pseudo-documents vectors formed from weighted combinations of terms, and documents are ordered by their similarity to the query. Initial tests find this automatic method very promising.

Comparing and combining the effectiveness of latent semantic indexing and the ordinary vector space model for information retrieval

Abstract A retrieval system was built to find individuals with appropriate expertise within a large research establishment on the basis of their authored documents. The expert-locating system uses a new method for automatic indexing and retrieval based on singular value decomposition, a matrix decomposition technique related to factor analysis. Organizational groups, represented by the documents they write, and the terms contained in these documents, are fit simultaneously into a 100-dimensional “semantic” space. User queries are positioned in the semantic space, and the most similar groups are returned to the user. Here we compared the standard vector-space model with this new technique and found that combining the two methods improved performance over either alone. We also examined the effects of various experimental variables on the systems retrieval accuracy. In particular, the effects of: term weighting functions in the semantic space construction and in query construction, suffix stripping, and using lexical units larger than a single word were studied.

A New Formative Assessment Technology for Reading and Writing

Advances in assessment technologies are affording teachers and students new ways to efficiently assess and track achievement while also better promoting learning. WriteToLearn is one such technology, a Web-based tool that integrates practice and assessment in reading comprehension with writing about what is learned. Based on the principle of immediate feedback, WriteToLearn is a combination of summative and formative assessment tools that seeks to encourage, instruct, and reward progress in reading and writing while it is happening. It does this by providing students with instant, computer-generated evaluations of the substantive content and expository quality of writing about what they are learning. Its real-time and long-term reports about student activity and progress give teachers and schools rich information for guiding classroom instruction and curricular decisions. This article discusses the motivation for and design of WriteToLearn, as well as studies of its accuracy, reliability, and effectiveness in the classroom.

Technology as a tool for leadership development: Effectiveness of automated web-based systems in facilitating tacit knowledge acquisition.

The effectiveness of emerging technology in helping to develop the tacit or experience-based knowledge needed for effective leadership performance was demonstrated in an on-line environment for discussion and training. One hundred and twenty-seven military students participated in three 20-minute discussions in one of three learning environments: standard classroom; standard on-line discussion; and discussion assisted by semantic technology. Consistent with expectations, semantic technology-supported learning resulted in greater discussion participation and training performance with discussion participation mediating the relationship between the learning environment and training satisfaction. An interaction between learning goal orientation (LGO) and learning environment on tacit knowledge performance showed that face-to-face conditions may help those with low LGO. Implications for improving tacit knowledge acquisition and technology-supported leadership development practices are discussed.