The features of text mining such as visualization and summarization are becoming common in software applications. Different areas process documents using different techniques.The work done here has been to design a text mining tool for molecular interactions in Arabidopsis Thaliana that gives accurate interactions and also saves the time. We proposed modifications to produce more knowlege outcomes . The tool created is very effective that performs text mining tasks very accurately and clearly.
We found that by using this tool there is no need to read whole documents related to Arabidopsis Thaliana, infact we can just enter name of molecule i.e, gene, transcription factors, protein or enzyme and our desired results will be displayed alongwith the title and link of document.
Although the study has reached its aims, there were some unavoidable limitations and short comings. First, while mining the text the overlapping words were also mined which resulted in poor mining. Second, some documents were not loaded properly which made it difficult to mine the text. Third, while exporting the mined text using configurable exporter the interactions in chunks were not in the sequence so there was a need of formatting.
We are planning to add more functionality to this tool like mining online documents and displaying our results in the form of flow chart or diagram. Moreover we are planning to design an algorithm which will be helpful for mining the desired information related to Arabidopsis Thaliana.