SOPHIA in Enterprise Track

task). Given a topic our task was to find an ordered list of up to 100 experts (from a predefined list of candidate experts) and for every expert create an ordered list of up to 20 support documents. Support document should prove that given person is indeed an expert in the domain presented by the topic. We implemented 3 algorithms to solve this task which resulted in 3 runs sophiarun1, sophiarun2 and sophiarun3. All runs are based on Contextual Document Clustering (CDC) algorithm [1,2] applied to a part of W3C document corpus. Document clustering W3C collection contains documents of different types. In our experiments we used only two document types: www and lists. Examples of www documents are drafts and final versions of official W3C documents, slides from presentations given by W3C members and so on. Documents of lists type are e-mails. We split www documents into parts, based on 1000 word long segments and considered every part as a separate document. We didn’t split mails (lists type documents)