| Interactive answering system is based on constructivism learning theory,distancelearning interaction theory, knowledge management theory. Based on the condition andthe real learning needs of self-taught student,we use the more popular searchtechnology and integrate disciplinary ontology database and full-text retrievaltechnology in order that this system should be able to understand Chinese naturallanguage and become more user-friendly.According to functional requirements and the actual retrieval demand from theuser, we combine the full-text search engine Lucene with a word segmentationanalyzer which is suitable for both Chinese and English. When system begins to buildthe index for resources, firstly, the system uses the vocabulary of the subject ontologydatabase and word library of Lucene to split words that users input and then startsindexing. When users retrieve resources by inputted words, the answering system willbe first to use the concept in the ontology library to analyzer the words that users input,and then get keywords to search. Secondly, it will use Lucene’s word analyzer to splitthe user’s input to get keywords and then use these keywords to search system’s indexin order to get resources that is correlative to user’s demand. |
