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Towards Automatic Extraction of Event and Place Semantics from Flickr Tags

The group formation algorithm deals with message loss by allowing every state in the finite state machine to time out while having a minimal effect on other nodes. For ex- ample, if a master node does not hear back from enough neighbors, it will time out (shown as TO in Figure 2) and transition back into the Need Group state. Nodes that had responded to the master cannot respond to any other master until they hear back from the current one. If they never hear back, they time out and go back to the Need Group state. The algorithm adds some. | Towards Automatic Extraction of Event and Place Semantics from Flickr Tags Tye Rattenbury Nathaniel Good and Mor Naaman Yahoo Research Berkeley Berkeley CA USA tye ngood mor @yahoo-inc.com ABSTRACT We describe an approach for extracting semantics of tags unstructured text-labels assigned to resources on the Web based on each tag s usage patterns. In particular we focus on the problem of extracting place and event semantics for tags that are assigned to photos on Flickr a popular photo sharing website that supports time and location latitude longitude metadata. We analyze two methods inspired by well-known burst-analysis techniques and one novel method Scale-structure Identification. We evaluate the methods on a subset of Flickr data and show that our Scale-structure Identification method outperforms the existing techniques. The approach and methods described in this work can be used in other domains such as geo-annotated web pages where text terms can be extracted and associated with usage patterns. Categories and Subject Descriptors H.1.m MODELS AND PRINCIPLES Miscellaneous General Terms Algorithms Measurement Keywords tagging systems event identification place identification tag semantics word semantics 1. INTRODUCTION User-supplied tags textual labels assigned to content have been a powerful and useful feature in many social media and Web applications e.g. Flickr del.icio.us Technorati . Tags usually manifest in the form of a freely-chosen short list of keyword associated by a user with a resource such as a photo web page or blog entry. Unlike category- or ontology-based systems tags result in unstructured knowledge - they have no a-priori semantics. However it is precisely the unstructured nature of tags that enables their utility. For example tags are probably easier to enter than picking categories from an ontology tags allow for greater Also affiliated with UC Berkeley Computer Science Dept. .Also affiliated with UC Berkeley School of Information. Permission