We discuss Feature Latent Semantic Analysis (FLSA), an extension to Latent Semantic Analysis (LSA). LSA is a statistical method that is ordinarily trained on words only; FLSA adds to LSA the richness of the many other linguistic features that a corpus may be labeled with. We applied FLSA to dialogue act classification with excellent results. We report results on three corpora: CallHome Spanish,...

This study attempted to determine the types of semantic change of the selected Cebuano words from the written texts, specifically the Bisaya magazine and spoken language of Cebuano speakers aged 15 – 40 years old living in Cebu province. Twenty (20) Cebuano words were analyzed using Campbell’s (1998) and Crowley’s (1997) classifications of the semantic change. The results revealed that metaphor...

Contextual spelling errors are defined as the use of an incorrect, though valid, word in a particular sentence or context. Traditional spelling checkers flag misspelled words, but they do not typically a t tempt to identify words that are used incorrectly in a sentence. We explore the use of Latent Semantic Analysis for correcting these incorrectly used words and the results are compared to ear...

This paper presents the design considerations of a tool aiming at providing formative feedback. The tool uses Latent Semantic Analysis, to automatically generate reference models and provide learners a means to compare their conceptual development against these models. The design of the tool considers a theoretical background which combines research on expertise development, knowledge creation,...

We present a new measure of liquidity known as “latent liquidity” and apply it to a unique corporate bond database. Latent liquidity is defined as the weighted average turnover of investors who hold a bond, where the weights are the fractional investor holdings. It can be used to measure liquidity in markets with sparse transactions data. For bonds that trade frequently, our measure has predict...

This paper elaborates on the design of a computer-based service to support conceptual development. Our ambition is provide learners a way to compare their conceptual development against different reference models, so they recognize the limits of their expertise. These models are (semi) automatically generated from learning materials and learner text inputs using Latent Semantic Analysis, a tech...

This paper is concerned with the problem of automatic essay grading, where the task is to grade student written essays given course materials and a set of humangraded essays as training data. Latent Semantic Analysis (LSA) has been used extensively over the years to accomplish this task. However, the major limitation of LSA is that it only retains the frequency of words by disregarding the word...

The underlying idea of latent semantic analysis (LSA) (Deerwester et al. 1990) is that the aggregate of all of the contexts in which a given word does and does not appear provides a set of constraints that determines the similarity of meanings for words, and sets of words, to each other (Landauer et al. 1998). Thus, when two terms occur in contexts of similar meaning, even if they never occur i...

A Latent Semantic Index (LSI) was constructed from arguments made by Navy officers concerning events in an Anti-Air Warfare scenario. A model based on LSI factor values predicted level of domain expertise with 89% accuracy. The LSI factor space was reduced using MDS to five dimensions: aircraft route, aircraft response, kinematics, localization, and an unclassifiable element. Arguments in the l...