Automatic Indexing Framework for Context Aware Personal Document Management System
Keywords:
Information Retrieval, Personal Document Management, Formal Concept Analysis (FCA), Incremental Formal Concept Analysis, Context Aware Document Retrieval, Automatic Indexing, Document ClusteringAbstract
Today managing files in a personal computer has the same magnitude as managing the World Wide Web due to the dynamic nature of the file system [1]. Even searching for files over a file system is time consuming because finding a file on hard disk is a long-running task. Every file on the disk has to be read with dangling pointers to files which no longer exist because they have been changed, moved or deleted. This makes the user frustrated. Personal document management is the activity of managing a collection of digital documents by the owner of the documents.
This consists of creation, organization, finding and maintenance of documents. Information, especially digital information, is no longer a scarce resource; information exists in abundance and human time and attention have now become the scarce resource [2]. Information overload is now a recognized problem as people struggle to manage the increasing quantities of information they need to deal with on a daily basis [3]. Therefore, an on demand software agent comes necessary to manage the file system and retrieve information that the User needs.
This research proposes a framework that manages semi-structured file collection based on Formal Concept Analysis (FCA). Formal Concept Analysis has been applied in document retrieval in different contexts. Solutions like Conceptual Email Manager [4] and DOCCO [5] do not support dynamic insertions of documents (Extents) to their concept lattice. These tools require algorithms to re-run in order to rebuild the index which is costly. In this work concept lattice is generated incrementally on a document collection and stored in a database making the hierarchical structure compact to facilitate parallel insert and search. The proposed framework utilizes database queries and functions complemented with inverted index which facilitates fast document retrieval and reduce the downtime of costly updates on the master index.
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