Web-a-where: geotagging web content

By E. Amitay, Nadav Har'El, Ron Sivan, Aya Soffer. Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2004

644 citations recorded by the source corpus.

Subfields: Geography, Planning and Development, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/1fb53788bd052bc09e727aaab8d381b8ff9a201d

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Citations in the corpus

Efficient query processing in geographic web search engines (2006, methodology): “Subsequent work in [8, 12, 1, 30] proposed additional techniques, including use of hyperlinks and site structure.”
Hybrid index structures for location-based web search (2005, background): “Recently, quite a few researchers have studied this problem [1,3,4,13,18].”
Semi-supervised User Geolocation via Graph Convolutional Networks (2018, background): “There are three main text-based approaches to geolocation: (1) gazetteer-based models which map geographical references in text to location, but ignore non-geographical references and vernacular uses of language (Rauch et al., 2003; Amitay et al., 2004; Lieberman et al., 2010); (2) geographical topi”
Toponym resolution in text: annotation, evaluation and applications of spatial grounding (2007, background): “(2003) (the authors claim they use proximity, but do not give details); Amitay et al. (2004).”
Geolocation Prediction in Social Media Data by Finding Location Indicative Words (2012, background): “In the information retrieval community, e.g. web pages (Ding et al., 2000; Amitay et al., 2004; Zong et al., 2005; Silva et al., 2006), search query logs (Wang et al., 2005; Backstrom et al., 2008), Wikipedia edit logs (Lieberman and Lin, 2009) and Flickr image tags (Crandall et al., 2009;…”
Towards automatic extraction of event and place semantics from flickr tags (2007, background): “[2, 6, 8]) at extracting geographic information for a web page, based on the page links and network properties, as well as geographic terms that appear on the page.”
TwitterStand: news in tweets (2009, methodology): “In terms of tweet content, we perform what is called geo-tagging [1] on each tweet’s text, as well as any articles linked from the tweet (i.e., the tweet’s artifacts).”
You are where you tweet: a content-based approach to geo-locating twitter users (2010, background): “studies of blogs [11, 15], webpages [7], search engine query logs [8], and even web users [13].”
IR-Tree: An Efficient Index for Geographic Document Search (2011, methodology): “Our geocoder is developed based on a proprietary geographic ontology that covers about 129,784 worldwide locations [19], and it employs the focus-detecting algorithm [1] to locate one location for each document.”