SemTag and seeker: bootstrapping the semantic web via automated semantic annotation

By Steve Dill, Nadav Eiron, David Gibson, Daniel F. Gruhl, Ramanathan V. Guha, A. Jhingran, Tapas Kanungo, Sridhar Rajagopalan, Andrew Tomkins, J. Tomlin and 1 more. The Web Conference, 2003

595 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/f60ff1e240be1b1e74c164d0ef4fb2d67f0cbdc3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Daniel S. Weld
2. Hannaneh Hajishirzi
3. Luke S. Zettlemoyer
4. Mohit Bansal
5. Percy Liang
6. Dan Roth
7. Yejin Choi
8. Fei Wu

In Information Systems

1. Daniel S. Weld
2. Philipp Cimiano
3. Fei Wu
4. Steffen Staab
5. Luke S. Zettlemoyer
6. Andrew Tomkins
7. Siegfried Handschuh
8. Ravi Kumar

In Management Science and Operations Research

1. Hannaneh Hajishirzi
2. Pablo N. Mendes
3. Amit P. Sheth
4. Ramanathan V. Guha
5. Ravi Kumar
6. Maarten de Rijke
7. Christian Bizer
8. Sunita Sarawagi

Citations in the corpus

• Semantic Annotation, Indexing, and Retrieval (2003, methodology): “Perhaps the closest - in terms of goals and architecture - to KIM is the SemTag system [27], which performs large-scale semantic annotation with respect to the TAP ontology.”
• Adding semantics to microblog posts (2012, methodology): “A simple and frequently taken approach for linking text to concepts is to perform lexical matching between (parts of the text) and the concept titles [10, 26], an approach related to keyword-based interfaces to databases [38].”
• Semantic (Web) Technology In Action: Ontology Driven Information Systems for Search, Integration and Analysis (2003, background): “A somewhat related non-Semagix business intelligence [IBMWF] application has demonstrated scalability by extracting metadata (albeit somewhat limited types of metadata with a significantly smaller ontology) from a billion pages [Dill et al 2003].”
• Joint Coreference Resolution and Named-Entity Linking with Multi-Pass Sieves (2013, methodology): “Our work also builds on a long trajectory of work in named entity resolution stemming from SemTag (Dill et al., 2003).”
• Towards the self-annotating web (2004, background): “…http://www.aifb.uni-karlsruhe.de/WBS 2Ontoprise GmbH, 76131 Karlsruhe, Germany http://www.ontoprise.com/ ABSTRACT The success of the Semantic Web depends on the availability of on­tologies as well as on the proliferation of web pages annotated with metadata conforming to these ontologies.”
• Autonomously semantifying wikipedia (2007, methodology): “TheSemTagandSeeker[10] systems perform automated semantic tagging of large corpora.”
• DBpedia spotlight: shedding light on the web of documents (2011, background): “SemTag [10] was the first Web-scale named entity disambiguation system.”
• Ontologies and the semantic web (2006, background): “, text) [16], and the automated annotation of both text [6] and images [5].”
• The predictive power of online chatter (2005, background): “IBM’s WebFountain project [13, 11] maintains large collections of online material, including postings from approx-”
• Annotating and searching web tables using entities, types and relationships (2010, background): “[10] S. Dill et al. SemTag and Seeker: Bootstrapping the semantic Web via automated semantic annotation.”
• Discovering Large Dense Subgraphs in Massive Graphs (2005, background): “IBM’s WebFountain project [18, 12] performs largescale analysis of unstructured information, including the web.”