CLUSTER GRAPH BASED MODEL FOR EXTRACTING AND SEARCHING ALGORITHM IN BIGDATA

摘要

Search systems that is used to search for information. Cite Seer was a search engine to search academic documents. Platforms are not available to discover algorithms in scholarly big data. The limitations of these search engines make the searching more difficult. Hence special purpose systems are used. Here proposes a search system to extract algorithm representations. Algorithms can be represented using pseudocode and algorithm procedures. Two methods are used for this purpose. The ways to extract textual metadata for each algorithm is discussed. Based on graph based clustering, context term is extracted. The metadata extraction is done using document element summarization. The synopsis is generated using topic modeling approach and context terms. Finally a synopsis comparison is done.