Annotating and searching web tables using entities, types and relationships

By Girija Limaye, Sunita Sarawagi, Soumen Chakrabarti. Proceedings of the VLDB Endowment, 2010

475 citations recorded by the source corpus.

Subfields: Information Systems, Management Science and Operations Research, Signal Processing

View Paper: https://www.semanticscholar.org/paper/53f5249ff2dc66a7a8a3ccabca24911e932a98b4

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Citations in the corpus

Compositional Semantic Parsing on Semi-Structured Tables (2015, background): “There have been several studies on analyzing or inferring the table schemas (Cafarella et al., 2008; Venetis et al., 2011; Syed et al., 2010; Limaye et al., 2010) and answering search queries by joining tables on similar columns (Cafarella et al., 2008; Gonzalez et al., 2010; Pimplikar and…”
Entity Linking with a Knowledge Base: Issues, Techniques, and Solutions (2015, background): “[119] proposed to simultaneously annotate table cells with entities, table columns with types and pairs of table columns with relations in a knowledge base.”
TABBIE: Pretrained Representations of Tabular Data (2021, background): “The staggering amount of structured relational data in the form of tables on the Internet has attracted considerable attention from researchers over the past two decades (Cafarella et al., 2008; Limaye et al., 2010; Venetis et al., 2011; Suchanek et al., 2007; Embley et al., 2006), with applications”
A Comprehensive Survey on Automatic Knowledge Graph Construction (2023, background): “[71], for instance, construct a factor graph for collective entity linking based on the TF-IDF algorithm that calculates the term frequency of entity labels with cell-text pairs and type labels with column-head pairs.”
YAGO2: A Spatially and Temporally Enhanced Knowledge Base from Wikipedia: Extended Abstract (2013, methodology): “These include KnowItAll and its successor TextRunner [4, 5], DBpedia [3], the Omnivore system [48], work on distilling Web tables and lists into facts [49, 50, 51], the ReadTheWeb project [52] the StatSnowball methods used for building EntityCube [53] and its follow-up project Probase [54], WikiNet ”
AIDA (2011, background): “Even structured Web data such as tables and lists in Web pages face this problem, as their cells merely contain names, often in abbreviated or otherwise non-canonical form (e.g., “Mac” instead of “Apple Macintosh”) [4, 11].”
InfoGather: entity augmentation and attribute discovery by holistic matching with web tables (2012, methodology): “Researchers have developed techniques to annotate web tables with column names and names of relationships [19, 14].”
KATARA: A Data Cleaning System Powered by Knowledge Bases and Crowdsourcing (2015, background): “(3) PGM is a supervised learning approach that requires training and tuning of a number of weights.”
Knowledge Graphs (2020, unknown): “For the purposes of enriching knowledge graphs, more recent approaches again apply distant supervision, first linking table cells to knowledge graph nodes, which are used to generate candidates for type and relation extraction [316, 364, 366].”
Ten Years of WebTables (2018, background): “Limaye, et al. [25] studied how to annotate web tables with the presence of entities in cells, attribute types and concepts; and the presence of relationships between attributes.”
Semantic Web in data mining and knowledge discovery: A comprehensive survey (2016, methodology): “[39] Persons, places, organizations / H No No Yes DBpedia, YAGO, WordNet /”
Biperpedia: An Ontology for Search Applications (2014, background): “Several recent efforts have focused on harnessing such tables [1, 4, 17, 25, 26].”
Constrained Semi-supervised Learning in the Presence of Unanticipated Classes (2016, methodology): “[79] proposed a system to use an existing catalog and type hierarchy for annotating table columns and cells.”
Knowledge Graphs 2021: A Data Odyssey (2021, background): “Information extraction from web tables has been addressed for a decade (e.g., [2, 17, 41]), but there is only limited work on the specific theme of quantities (e.g., [31] and our recent work [9, 10]).”