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A large amount of research, technical and professional documents are available today in digital formats. Digital libraries are created to facilitate search and retrieval of information supplied by the documents. These libraries may span an entire area of interest (e.g., computer science) or be limited to documents within a small organization. While tools that index, classify, rank and retrieve documents from such libraries are important, it would be worthwhile to complement these tools with information available on the Web. We propose one such technique that uses a topical crawler driven by the information extracted from a research document. The goal of the crawler is to harvest a collection of Web pages that are focused on the topical subspaces associated with the given document. The collection created through Web crawling is further processed using lexical and linkage analysis. The entire process is automated and uses machine learning techniques to both guide the crawler as well as analyze the collection it fetches. A report is generated at the end that provides visual cues and information to the researcher.