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62
Mining Human-Place Interaction Patterns from Location-Based Social Networks to Enrich Place Categorization Systems
"... Abstract. Place categorization plays an important role in location-based services as well as more recently in place-based geographic in-formation systems. Traditionally, such categorization systems are often designed following a top-down approach in which a group of experts or users assign a place t ..."
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of this perception are captured by location-based social network platforms. Contributions to these platforms, such as check-ins and reviews, enable a bottom-up approach to place categorization based on the actual interaction between humans and places. In this short pa-per, we outline selected advantages of a hybrid
Materials for an exploratory theory of the network society.
- The British Journal of Sociology
, 2000
"... ABSTRACT This article aims at proposing some elements for a grounded theor y of the network society. The network society is the social structure characteristic of the Information Age, as tentatively identi ed by empirical, cross-cultural investigation. It permeates most societies in the world, in v ..."
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Cited by 122 (0 self)
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of ows. And so to do an increasing number of alternative social practices (such as social movements) and personal interaction networks. However, the space of ows does include a territorial dimension, as it requires a technological infrastructure that operates from certain locations, and as it connects
A Service of zbw Leibniz-Informationszentrum Wirtschaft Leibniz Information Centre for Economics Exploring city social interaction ties in the big data era: Evidence based on location-based social media data from China
"... Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, ..."
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the geographical ties of urban network patterns by using social media users" mobility flows at a detailed spatial degree (the city-pair level) based on location-based social media (Weibo, a Chinese version of Twitter) data from China. At its heart a geo-tagged computational framework is designed to extract
Expertise identification using email communications
- In CIKM ’03: Proceedings of the twelfth international conference on Information and knowledge management
, 2003
"... A common method for finding information in an organization is to use social networks—ask people, following referrals until someone with the right information is found. Another way is to automatically mine documents to determine who knows what. Email documents seem particularly well suited to this ta ..."
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Cited by 124 (0 self)
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to this task of “expertise location”, as people routinely communicate what they know. Moreover, because people explicitly direct email to one another, social networks are likely to be contained in the patterns of communication. Can these patterns be used to discover experts on particular topics
Mining User Similarity from Semantic Trajectories
- In Proceedings of ACM SIGSPATIAL International Workshop on Location Based Social Networks
, 2010
"... In recent years, research on measuring trajectory similarity has attracted a lot of attentions. Most of similarities are defined based on the geographic features of mobile users ’ trajectories. However, trajectories geographically close may not necessarily be similar because the activities implied b ..."
Abstract
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Cited by 23 (5 self)
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social networks. The core of our proposal is a novel trajectory similarity measurement, namely, Maximal Semantic Trajectory Pattern Similarity (MSTP-Similarity), which measures the semantic similarity between trajectories. Accordingly, we propose a user similarity measurement based on MSTP
Mining graph patterns efficiently via randomized summaries
- PVLDB
"... Graphs are prevalent in many domains such as Bioinformatics, social networks, Web and cyber-security. Graph pattern mining has become an important tool in the management and analysis of complexly structured data, where example applications include indexing, clustering and classification. Existing gr ..."
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Cited by 7 (0 self)
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Graphs are prevalent in many domains such as Bioinformatics, social networks, Web and cyber-security. Graph pattern mining has become an important tool in the management and analysis of complexly structured data, where example applications include indexing, clustering and classification. Existing
Socially Relevant Venue Clustering from Check-in Data
"... ABSTRACT The recent proliferation of location-based social network services has resulted in an abundance of spatial-temporal data on user mobility. Understanding individual and collective mobility patterns is important for many applications. In this study, we examine the similarity of users based o ..."
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ABSTRACT The recent proliferation of location-based social network services has resulted in an abundance of spatial-temporal data on user mobility. Understanding individual and collective mobility patterns is important for many applications. In this study, we examine the similarity of users based
Network structure mining: locating and isolating core members in covert terrorist networks
- WSEAS Transactions on Information Science and Applications
, 2008
"... Abstract: Knowing patterns of relationship in covert (illegal) networks is very useful for law enforcement agencies and intelligence analysts to investigate collaborations among criminals. Previous studies in network analysis have mostly dealt with overt (legal) networks with transparent structures. ..."
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Cited by 2 (0 self)
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. Unlike conventional data mining that extracts patterns based on individual data objects, network structure mining is especially suitable for mining a large volume of association data to discover hidden structural patterns in criminal networks. Covert networks share some features with conventional (real
Predicting Link Strength In Online Social Networks
"... Social Media is a term that encompasses the platforms of New Media, but also implies the inclusion of systems like Facebook, and other things typically thought of as social networking. The idea is that they are media platforms with social components and public communication channels. Social media ar ..."
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are primarily Internet-based tools for sharing and discussing information among human beings. Data mining (the analysis step of the “Knowledge Discovery in Databases ” process, or KDD), is the process that attempts to discover patterns in large data sets. The overall goal of the data mining process
Concurrent Goal-oriented Co-clustering Generation in Social Networks
"... Abstract-Recent years, social network has attracted many attentions from research communities in data mining, social science and mobile etc, since users can create different types of information due to different actions and the information gives us the opportunities to better understand the insight ..."
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the insights of people's social lives. Co-clustering is an important technique to detect patterns and phenomena of two types of closely related objects. For example, in a location based social network, places can be clustered with regards to location and category, respectively and users can be clustered w
Results 1 - 10
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62
