An adaptive scheme for handling deletion spelling errors' for an intelligent e-learning system

Abstract

An adaptive scheme for handling spelling errors by an e-Iearner while responding to the e-Iearning system through typed-in single-word responses is presented in this paper. To simulate the behaviour of a human instructor, the system preprocesses the input word with respect to spelling errors due to wrong letter or missing letter. The appropriately encoded input is then to fed into a neural net that intelligently recognizes the correct response, in spite of minor spelling mistakes committed by the learner. Results show that the scheme intelligent recognises the misspelled words as expected to be done by a human instructor.

Optimized web search results through additional retrieval lists inferred using WordNet similarity measure

“…The Query Preprocessing is essential and considered to be indispensable to refine the given query and eliminates the unnecessary words to make the search process easy and reach the target document which the user actually intended [4]. The "Stop-words" (Ex: a, an, the, in, on etc) will be removed as their contribution in identifying the target documents are minimal and it is well known through many literature.…”