computer aided training of text comprehension
Project management at the University of Würzburg:
The main source of knowledge for students are texts, i.e. students mainly learn by reading. It has long been noticed that summarizing improves text comprehension processes and by this the efficiency of learning from texts. To this end a computational aided system is being developed, that assists by writing of summaries in German language.
The system uses Latent Semantic Analysis (LSA), a computational model of word and documents similarities. LSA analyzes the co-occurrence of words in huge corpora and generates a high-dimensional vector space in which single words, sentences and even paragraphs are commonly represented by corresponding vectors. Thus, the vector of a word (or a document) represents its co-occurrence with all other words (documents). Accordingly, the vectors can be regarded as representing the meaning of words and paragraphs at least to the extent to which the meaning of a text is determined by its use.
The project aims at creating semantic vector spaces for German corpora in different subjects in order to use them for a tutorial program for writing summaries. Our work strongly profits from close cooperation with the LSA research group and the
Projekt period: from 09.2005 to 08.2007
DFG ,Granting date: 28.06.2005