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Structural information (such as layout and look-and-feel) has been extensively used in the literatuce for extraction of interesting or relevant data, efficient storage, and query optimization. Traditionally, tree models (such as DOM trees) have been used to represent structural information, especially in the case of HTML and XML documents. However,(More)
This paper proposes an algorithm to hierarchically cluster documents. Each cluster is actually a cluster of documents and an associated cluster of words, thus a document-word co-cluster. Note that, the vector model for documents creates the document-word matrix, of which every co-cluster is a submatrix. One would intuitively expect a submatrix made up of(More)
This paper introduces <i>generalised disjunctive association rules</i> such as "People who buy bread also buy butter jam", and "People who buy <b>either</b> raincoats <b>or</b> umbrellas also buy flashlights". A <i>generalised disjunctive association rule</i> allows the disjunction of conjuncts, "People who buy jackets also buy bow ties <b>or</b> neckties(More)
Nearly two decades of research in the area of Inductive Logic Programming (ILP) have seen steady progress in clarifying its theoretical foundations and regular demonstrations of its applicability to complex problems in very diverse domains. These results are necessary, but not sufficient, for ILP to be adopted as a tool for data analysis in an era of very(More)
Entity annotation involves attaching a label such as 'name' or 'organization' to a sequence of tokens in a document. All the current rule-based and machine learning-based approaches for this task operate at the document level. We present a new and generic approach to entity annotation which uses the inverse index typically created for rapid keyword based(More)
Lack of supervision in clustering algorithms often leads to clusters that are not useful or interesting to human reviewers. We investigate if supervision can be automatically transferred to a clustering task in a target domain, by providing a relevant supervised partitioning of a dataset from a different source domain. The target clustering is made more(More)
Machine-generated documents containing semi-structured text are rapidly forming the bulk of data being stored in an organisation. Given a feature-based representation of such data, methods like SVMs are able to construct good models for information extraction (IE). But how are the feature-definitions to be obtained in the first place? (We are referring here(More)
Enterprises are increasingly using social media forums to engage with their customer online-a phenomenon known as Social Customer Relation Management (Social CRM). In this context, it is important for an enterprise to identify " influential authors " and engage with them on a priority basis. We present a study towards finding influential authors on Twitter(More)
Typical commercial Web sites publish information from multiple back-end data sources; these data sources are also updated very frequently. Given the size of most commercial sites today, it becomes essential to have an automated means of checking for correctness and consistency of data. The eShopmonitor allows users to specify items of interest to be(More)