Automated Semantic Analysis of Schematic Data: Learning-based Techniques for Scalable and Automated Semantic Understanding of Template Generated Schematic Web Content - Softcover

Inhaltsangabe

Content in numerous data sourcesare not directly amenable to machine processing.This book describes techniques for automated semantic analysis ofschematic content which are characterized by being populated from backenddatabases.Starting with a seed set of hand-labeled instances of semanticconcepts in a set of HTML documents, a technique is devised thatbootstraps an annotation process for automatic identification ofconcept instances present in other documents. The technique exploitsthe observation that semantically related items in schematic HTMLdocuments exhibit consistency in presentation style and spatiallocality to learn statistical concept models, using light-weightsemantic features. This model directs the annotation of diverseWeb documents possessing similar content semantics.The power of these techniques is demonstrated through applications developedfor real-life problems that includeaudio-based assistive browsing for non-visual Web access,focused browsing on handhelds with semantic bookmarks, text data cleaning,and accurate identification of remote homologs ofbiological protein sequences.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.