標(biāo)題: Titlebook: Big Data Analytics in the Social and Ubiquitous Context; 5th International Wo Martin Atzmueller,Alvin Chin,Christoph Trattner Conference pr [打印本頁(yè)] 作者: rupture 時(shí)間: 2025-3-21 18:44
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作者: 間諜活動(dòng) 時(shí)間: 2025-3-22 00:01
https://doi.org/10.1007/978-94-009-8179-9ring, and topic detection. State-of-the-art NERC systems are based on supervised machine learning and hence need to be trained on (manually) annotated corpora. However, annotated corpora hardly exist for non-standard languages and labeling additional data manually is tedious and costly. In this arti作者: headlong 時(shí)間: 2025-3-22 01:50
https://doi.org/10.1007/978-94-009-8179-9ing it to extract insights. But the relevance of such data to see beyond the present is not clear. We present efforts to predict future events based on web intelligence – data harvested from the web?– with specific emphasis on social media data and on timed event mentions, thereby quantifying the pr作者: Endoscope 時(shí)間: 2025-3-22 08:21
Introduction to Algebraic Geometryhreatened by high levels of member withdrawal. In this paper we borrow ideas from topic analysis to study editor activity on Wikipedia over time using latent space analysis, which offers an insight into the evolving patterns of editor behaviour. This latent space representation reveals a number of d作者: 正論 時(shí)間: 2025-3-22 11:24
Introduction to Algebraic Geometryasures such as Focus, Entropy and Spread have been applied to describe geospatial characteristics of social media contents. In this paper, we draw the attention to the fact that these popular measures do not necessarily show the geographic relevance or dependence of social content, but mix up geogra作者: A精確的 時(shí)間: 2025-3-22 15:25 作者: 芭蕾舞女演員 時(shí)間: 2025-3-22 20:10
,Géométrie diophantienne multiprojective, introduces a method for discovering . in smart water meter time series. Habits are household activities that recur in a predictable way, such as watering the garden at 6?am twice a week. Discovering habit patterns automatically is a challenging data mining task. Habit patterns are not only periodic作者: fleeting 時(shí)間: 2025-3-23 00:53
Yuri V. Nesterenko,Patrice Philipponper investigate road surface monitoring with smartphones equipped with GPS and inertial sensors: accelerometer and gyroscope. In this study we describe the conducted experiments with data from the time domain, frequency domain and wavelet transformation, and a method to reduce the effects of speed, 作者: 青石板 時(shí)間: 2025-3-23 05:07 作者: Defiance 時(shí)間: 2025-3-23 06:28
Criteria for algebraic independence,ons of location prediction include location-based services, resource allocation, handoff management in cellular networks, animal migration research, and weather forecasting. Most current techniques try to predict the next location of moving objects such as vehicles, people or animals, based on their作者: 安裝 時(shí)間: 2025-3-23 10:14
Big Data Analytics in the Social and Ubiquitous Context978-3-319-29009-6Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: ANTIC 時(shí)間: 2025-3-23 15:59 作者: Glossy 時(shí)間: 2025-3-23 20:33
978-3-319-29008-9Springer International Publishing Switzerland 2016作者: 抵制 時(shí)間: 2025-3-24 01:00 作者: 連鎖 時(shí)間: 2025-3-24 06:10 作者: CHANT 時(shí)間: 2025-3-24 09:50 作者: Oscillate 時(shí)間: 2025-3-24 14:10
A Latent Space Analysis of Editor Lifecycles in Wikipedia,ow that long term editors generally have more diversified edit preference and experience relatively soft evolution in their editor profiles, while short term editors generally distribute their contribution at random among the namespaces and categories of articles and experience considerable fluctuation in the evolution of their editor profiles.作者: 襲擊 時(shí)間: 2025-3-24 15:38
On Spatial Measures of Geographic Relevance for Geotagged Social Media Content,ic effects alone. By means of an assessment, based on Twitter data collected over a time span of six weeks, we highlight potential misinterpretations and we furthermore propose normalized measures which show less dependency on the underlying user population and are able to mitigate the effect of outliers.作者: LAITY 時(shí)間: 2025-3-24 19:38 作者: 延期 時(shí)間: 2025-3-25 00:11
Yuri V. Nesterenko,Patrice Philipponods we are able to build a real time multi class road anomaly detector. We obtained a consistent accuracy of .90?% on detecting severe anomalies regardless of vehicle type and road location. Local road authorities and communities can benefit from this system to evaluate the state of their road network pavement in real time.作者: defray 時(shí)間: 2025-3-25 04:07 作者: 小臼 時(shí)間: 2025-3-25 08:17
RoADS: A Road Pavement Monitoring System for Anomaly Detection Using Smart Phones,ods we are able to build a real time multi class road anomaly detector. We obtained a consistent accuracy of .90?% on detecting severe anomalies regardless of vehicle type and road location. Local road authorities and communities can benefit from this system to evaluate the state of their road network pavement in real time.作者: BRAWL 時(shí)間: 2025-3-25 14:49 作者: FRET 時(shí)間: 2025-3-25 19:43
Formation and Temporal Evolution of Social Groups During Coffee Breaks,ng to phases of the conference. Specifically, we investigate group formation and evolution using real-world data collected at the LWA 2010 conference utilizing the Conferator system, and discuss patterns according to different phases of the conference.作者: Misgiving 時(shí)間: 2025-3-25 23:20
Conference proceedings 2016dge Discovery in Databases (ECML-PKDD 2014) in Nancy, France; and the 5thInternational Workshop on Modeling Social Media (MSM 2014) that was held onApril 8, 2014 in conjunction with ACM WWW in Seoul, Korea..作者: botany 時(shí)間: 2025-3-26 03:18
0302-9743 e ofKnowledge Discovery in Databases (ECML-PKDD 2014) in Nancy, France; and the 5thInternational Workshop on Modeling Social Media (MSM 2014) that was held onApril 8, 2014 in conjunction with ACM WWW in Seoul, Korea..978-3-319-29008-9978-3-319-29009-6Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: coalition 時(shí)間: 2025-3-26 07:48 作者: 幻想 時(shí)間: 2025-3-26 09:07
Using Wikipedia for Cross-Language Named Entity Recognition,esults in a partially annotated corpus that is likely to contain unannotated entities. To learn from such partially annotated data, we devise two simple extensions of hidden Markov models and structural perceptrons. Empirically, we observe that using the automatically generated data leads to more ac作者: Between 時(shí)間: 2025-3-26 13:07 作者: agglomerate 時(shí)間: 2025-3-26 17:36 作者: MEEK 時(shí)間: 2025-3-26 22:55
Context-Aware Location Prediction,ation of vehicles. We use five contextual features related to either the object environment or its current movement data: current location; object velocity; day of the week; weather conditions; and traffic congestion in the area. Our algorithm incorporates these context features into its trajectory-作者: 暗語(yǔ) 時(shí)間: 2025-3-27 04:08
https://doi.org/10.1007/978-94-009-8179-9esults in a partially annotated corpus that is likely to contain unannotated entities. To learn from such partially annotated data, we devise two simple extensions of hidden Markov models and structural perceptrons. Empirically, we observe that using the automatically generated data leads to more ac作者: 吞噬 時(shí)間: 2025-3-27 07:45
https://doi.org/10.1007/978-94-009-8179-9crucially – the reported timeframe for the occurrence of the event discussed – whether it be in the past, present, or future. Tweets (Twitter posts) that mention an event to occur reportedly in the future prove to be important predictors. These signals are enhanced by cross referencing with the frag作者: 確認(rèn) 時(shí)間: 2025-3-27 11:41
,Géométrie diophantienne multiprojective,d by a nonnegative matrix factorization algorithm (NMF). NMF is used to learn dictionaries of usages that can be exploited in order to characterize user mobility and station patterns. The relevance of the extracted dictionaries is then assessed by using them to cluster users and stations. This analy作者: 單調(diào)性 時(shí)間: 2025-3-27 14:56 作者: Medicaid 時(shí)間: 2025-3-27 18:14
Big Data Analytics in the Social and Ubiquitous Context5th International Wo作者: Decline 時(shí)間: 2025-3-27 23:46 作者: 辭職 時(shí)間: 2025-3-28 02:06 作者: 摘要 時(shí)間: 2025-3-28 09:51 作者: Modify 時(shí)間: 2025-3-28 14:01 作者: Nerve-Block 時(shí)間: 2025-3-28 17:12
Formation and Temporal Evolution of Social Groups During Coffee Breaks,e-to-face proximity. We first analyze statistical properties of group evolution, e.g., individual activity and typical group sizes. After that, we define a set of specific group evolution events. These are analyzed in the context of an academic conference, where we provide different patterns accordi作者: 無(wú)脊椎 時(shí)間: 2025-3-28 22:14
A Habit Detection Algorithm (HDA) for Discovering Recurrent Patterns in Smart Meter Time Series, introduces a method for discovering . in smart water meter time series. Habits are household activities that recur in a predictable way, such as watering the garden at 6?am twice a week. Discovering habit patterns automatically is a challenging data mining task. Habit patterns are not only periodic作者: Antagonism 時(shí)間: 2025-3-28 23:00
RoADS: A Road Pavement Monitoring System for Anomaly Detection Using Smart Phones,per investigate road surface monitoring with smartphones equipped with GPS and inertial sensors: accelerometer and gyroscope. In this study we describe the conducted experiments with data from the time domain, frequency domain and wavelet transformation, and a method to reduce the effects of speed, 作者: 尊重 時(shí)間: 2025-3-29 07:03
Mining Ticketing Logs for Usage Characterization with Nonnegative Matrix Factorization,ent fields like social sciences, urbanism or geography. With the increasing number of probes tracking human locations, like RFID pass for urban transportation, road sensors, CCTV systems or cell phones, mobility data are exponentially growing. Mining the activity logs in order to model and character
