Automated Semantic Analysis of Schematic Data
Learning-based Techniques for Scalable and Automated Semantic Understanding of Template Generated Schematic Web Content
(Sprache: Englisch)
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 backend databases.Starting with a seed set of...
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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 backend databases.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 diverse Web documents possessing similar content semantics.The power of these techniques is demonstrated through applications developed for real-life problems that includeaudio-based assistive browsing fornon-visual Web access,focused browsing on handhelds with semantic bookmarks, text data cleaning, and accurate identification of remote homologs of biological protein sequences.
Autoren-Porträt von Saikat Mukherjee
Saikat Mukherjee received his Ph.D. from State University ofNew York, Stony Brook, in 2005 and is currently a ResearchScientist at Siemens Corporate Research, USA. He is interested insemantic analysis of unstructured text data using ontology-basedtechniques, machine learning, and natural languageprocessing.
Bibliographische Angaben
- Autor: Saikat Mukherjee
- 2008, 108 Seiten, Maße: 15,1 x 22,3 cm, Kartoniert (TB), Englisch
- Verlag: VDM Verlag Dr. Müller e.K.
- ISBN-10: 3639026748
- ISBN-13: 9783639026740
Sprache:
Englisch
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