Towards automatic extraction of event and place semantics from flickr tags
By Tye Rattenbury, Nathaniel Good, Mor Naaman. 2007
548 citations recorded by the source corpus.
Subfields: Geography, Planning and Development, Information Systems, Natural Language Processing, Signal Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Geography, Planning and Development
- Makoto Okazaki
- Takeshi Sakaki
- Yutaka Matsuo
- L. Kennedy
- Mor Naaman
- Roelof van Zwol
- Luis Gravano
- Hila Becker
In Information Systems
- Kristina Lerman
- L. Kennedy
- Mor Naaman
- Luis Gravano
- Hila Becker
- Tad Hogg
- Roelof van Zwol
- Vanessa Murdock
In Natural Language Processing
- L. Kennedy
- Mor Naaman
- Luis Gravano
- Hila Becker
- Roelof van Zwol
- Pavel Serdyukov
- Vanessa Murdock
- Yanwei Pang
In Signal Processing
- Makoto Okazaki
- Takeshi Sakaki
- Yutaka Matsuo
- L. Kennedy
- Mor Naaman
- Luis Gravano
- Hila Becker
- Roelof van Zwol
Citations in the corpus
- YFCC100M (2015, background): “In the past, geotagged media has been used to address a variety of research endeavors, such as location estimation [9], event detection [15], finding canonical views of places [4], and visual reconstruction of the world [17].”
- Generating diverse and representative image search results for landmarks (2008, methodology): “We can also use the techniques described in [19] to filter those images from Px that include tags that correspond to events.”
- Hip and trendy: Characterizing emerging trends on Twitter (2011, methodology): “Other research considers event and trend detection in other social media data, such as Flickr photographs (Becker, Naaman, & Gravano, 2010; Chen & Roy, 2009; Rattenbury et al., 2007).”
- How flickr helps us make sense of the world: context and content in community-contributed media collections (2007, methodology): “In [19] we provide additional details and evaluation on SSI and other methods for extracting these semantics from Flickr tags.”
- Social dynamics of Digg (2010, background): “Analyzing records of complex social activity can identify communities and important individuals within them [4], suggest relevant readings [21], and identify events [23] and trends [18,26].”
- Placing flickr photos on a map (2009, methodology): “In particular the reverse problem of discovering important landmarks and events, given a geographic co-ordinate has been studied extensively [1, 17, 13].”
- Tweet Analysis for Real-Time Event Detection and Earthquake Reporting System Development (2013, background): “Rattenbury et al. [30] specifically examines the problem of extracting place and event semantics for tags that are assigned to photographs on Flickr.”
- Separating Self-Expression and Visual Content in Hashtag Supervision (2017, background): “Other directions for future work include modeling user metadata [5] as well as spatial and temporal patterns [19].”
- The New Data and New Challenges in Multimedia Research (2015, background): “In the past, geotagged media has been used to address a variety of research endeavors, such as location estimation [19], event detection [20], finding canonical views of places [21], and visual reconstruction of the world [22].”
- Earthquake shakes Twitter users: real-time event detection by social sensors (2010, background): “Rattenbury et al. [22] specifically examined the problem of extracting place and event semantics for tags that are assigned to photographs on Flickr.”
- Photo2Trip: generating travel routes from geo-tagged photos for trip planning (2010, background): “[10] mined city landmarks from blogs by exploiting graphic models, while [8], [13], [11] and [5] attempted to visualize, recognize, describe and summarize a scene or a landmark by leveraging geo-tagged photos.”
- Flickr tag recommendation based on collective knowledge (2008, unknown): “Rattenbury et al. describe an approach for extracting event and place semantics of tags [18].”
- Learning similarity metrics for event identification in social media (2010, background): “Directly related to our problem, recent studies [11, 31] analyzed temporal and spatial tag distribution to identify tags corresponding to events.”