ppxscal/embedding_network huggingface dataset:
Characterizing User Groups in Online Social Networks
Authors: László Gyarmati, Tuan Anh Trinh
Venue: Proceedings of the 15th Open European Summer School and IFIP TC6.6 Workshop on The Internet of the Future (2009)

The users' role is crucial in the development, deployment and the success of online social networks (OSNs). Despite this fact, little is known and even less has been published about user activities in the operating OSNs. In this paper, we present a large scale measurement analysis of user behaviour, in terms of time spent online, in some popular OSNs, namely Bebo, Flixster, MySpace, and Skyrock, and characterise user groups in OSNs. We used more than 200 PlanetLab [1] nodes for our measurement, monitored more than 3000 users for three weeks by downloading repeatedly their profile pages; more than 100 million pages were processed in total. The main findings of the paper are the following. Firstly, we create a measurement framework in order to observe user activity. Secondly, we present cumulative usage statistics of the different OSNs. Thirdly, we classify the monitored users into different groups and characterise the common properties of the members. Finally, we illustrate the wide applicability of our datasets by predicting the sign out method of the OSN users.
Sentential structure and discourse parsing
Authors: Livia Polanyi, Chris Culy, Martin van den Berg, Gian Lorenzo Thione, David Ahn
Venue: Proceedings of the 2004 ACL Workshop on Discourse Annotation (2004)

In this paper, we describe how the LIDAS System (Linguistic Discourse Analysis System), a discourse parser built as an implementation of the Unified Linguistic Discourse Model (U-LDM) uses information from sentential syntax and semantics along with lexical semantic information to build the Open Right Discourse Parse Tree (DPT) that serves as a representation of the structure of the discourse (Polanyi et al., 2004; Thione 2004a, b). More specifically, we discuss how discourse segmentation, sentence-level discourse parsing, and text-level discourse parsing depend on the relationship between sentential syntax and discourse. Specific discourse rules that use syntactic information are used to identify possible attachment points and attachment relations for each Basic Discourse Unit to the DPT.
Multi-label learning by instance differentiation
Authors: Min-Ling Zhang, Zhi-Hua Zhou
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

Multi-label learning deals with ambiguous examples each may belong to several concept classes simultaneously, In this learning framework, the inherent ambiguity of each example is explicitly expressed in the output space by being associated with multiple class labels. While on the other hand, its ambiguity is only implicitly encoded in the input space by being represented by only a single instance. Based on this recognition, we hypothesize that if the inherent ambiguity can be explicitly expressed in the input space appropriately, the problem of multi-label learning can be solved more effectively. We justify this hypothesis by proposing a novel multi-label learning approach named INS-DIF. The core of INSDIF is instance differentiation that transforms an example into a bag of instances each of which reflects the example's relationship with one of the possible classes. In this way, INSDIF directly addresses the inherent ambiguity of each example in the input space. A two-level classification strategy is employed to learn from the transformed examples. Applications to automatic web page categorization, natural scene classification and gene functional analysis show that our approach outperforms several well-established multi-label learning algorithms.
SVR-Based Hybrid Model for a Rotary Dryer
Authors: Xin Wang, Chunhua Yang, Bin Qin
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

Modeling of rotary drying remains a challenging research topic due to the highly nonlinear and strongly interactive multivariable process. The first-principles model (white box) consisting of partial differential equations with several experimental parameters is very complex and the data-driven model (black box) is lack of transparency and the required depth and quality of industrial experimental data for model training is sometimes difficult to obtain. Therefore, a novel SVR-based hybrid modeling method applied to rotary drying is presented in this paper. First, a first-principles model is set and the unknown parameters of the model are estimated by using a SVR model, then an equivalent fuzzy rule is obtained from the SVR model to improve the transparency of model. The proposed SVR-based hybrid modeling method has been applied to a rotary dryer. The results indicate that the SVR-based hybrid model has better adaptation and prediction capabilities than its black box model.
Brief paper: An anti-windup technique for LMI regions
Authors: Brandon Hencey, Andrew Alleyne
Venue: Automatica (Journal of IFAC) (2009)

The anti-windup problem seeks to minimize closed loop performance deterioration due to input nonlinearities, such as saturation, for a given linear time-invariant plant and controller. This paper presents a linear matrix inequality (LMI) based method that attempts to minimize performance deterioration while explicitly restricting the anti-windup closed loop dynamics. The restriction placed on the dynamics is described via LMI regions, which is a form of regional pole placement. Finally, the techniques discussed in this paper are demonstrated on an electro-hydraulic testbed.
Within-Network Classification Using Local Structure Similarity
Authors: Christian Desrosiers, George Karypis
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (2009)

Within-network classification, where the goal is to classify the nodes of a partly labeled network, is a semi-supervised learning problem that has applications in several important domains like image processing, the classification of documents, and the detection of malicious activities. While most methods for this problem infer the missing labels collectively based on the hypothesis that linked or nearby nodes are likely to have the same labels, there are many types of networks for which this assumption fails, e.g., molecular graphs, trading networks, etc. In this paper, we present a collective classification method, based on relaxation labeling, that classifies entities of a network using their local structure. This method uses a marginalized similarity kernel that compares the local structure of two nodes with random walks in the network. Through experimentation on different datasets, we show our method to be more accurate than several state-of-the-art approaches for this problem.
Analyzing reading behavior by blog mining
Authors: Tadanobu Furukawa, Mitsuru Ishizuka, Yutaka Matsuo, Ikki Ohmukai, Koki Uchiyama
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

This paper presents a study of the various aspects of blog reading behavior. The analyzed data are obtained from a Japanese weblog hosting service, Doblog. Four kinds of social networks are generated and analyzed: citation, comment, trackback, and blogroll networks. In addition, the user log data are used to identify readership relations among bloggers. After analysis of more than 50,000 users for about two years, we reveal some interactions between social relations and readership relations. We first show that bloggers read other weblogs on a regular basis (50% of weblogs that are read at least three times are read every five times a user logs in). We call this relation a regular reading relation (RR relation). Then, prediction of RR relations is done using features from the four kinds of social networks. Lastly, information diffusion on RR relations is analyzed and characterized. Results of this study show that the blogs in RR relations have an important role in bloggers' activities. We find the features which have a correlation with RR relations.
Network of Multi-Agent Traffic Controllers
Authors: Ongard Sirisaengtaksin, Danil Safin
Venue: Proceedings of the 2009 IEEE International Conference on Networking, Architecture, and Storage (2009)

Driving through streets of an inner city such as a downtown area sometimes can be frustrating. One might have to wait for a traffic light to turn green at an intersection where there is no car on the cross street. Or, there may be a lot of cars on the cross street that must be cleared in order to make the traffic flowing. The objective of this project is to develop an intelligent traffic controller model to coordinate a network of traffic lights such that the flow of the traffic is maximized and the time of the traffic flow is minimized. We proposed to develop a model that implements multi-agents and fuzzy controllers on a network of computers. In the model, we created two types of agents, communication and computation agents for each traffic light at an intersection. In order to validate our model, we created a simulation test bed utilizing a cluster of computers where each node on the cluster represents traffic lights at an intersection. The simulation test bed also allows us to perform comparisons of our model to the other models.
Predictive QoS routing to mobile sinks in wireless sensor networks
Authors: Branislav Kusy, HyungJune Lee, Martin Wicke, Nikola Milosavljevic, Leonidas Guibas
Venue: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (2009)

We present an algorithm for data delivery to mobile sinks in wireless sensor networks. Our algorithm is based on information potentials, which we extend to account for mobility. We show that for local movement along edges in the communication graph, the information potentials can be adapted using a simple iterative distributed computation. However, for non-local movement, the potential field might change significantly, and iterative computation leads to packet loss and packet delivery delays. We address this problem by introducing the mobility graph, which encodes knowledge about likely mobility patterns within the network. The mobility graph can be extracted from training data and is used to predict future relay nodes for the mobile node. Using the mobility graph, we can precompute and efficiently store additional routing states in the network. This enables the algorithm to maintain uninterrupted data streams. We analyze the benefits of computing and maintaining a mobility graph, and show that the information contained therein can be used to improve routing reliability in experiments involving mobile sinks.
Variable-ratio digital frequency dividers: Analogue design methodology and phase noise analysis based on harmonic balance
Authors: Marco Detratti, Juan Pablo Pascual
Venue: International Journal of RF and Microwave Computer-Aided Engineering (2009)

A unifying analogue description of the operation principle of digital dividers is proposed. A simple switched-ring oscillator is used as the basic block to build a reference model of fixed-ratio dividers, which is extended to variable-ratio dividers, serving as a design guide. The concept of variable-ratio digital frequency dividers as switched-ring oscillators justifies the proposal of a procedure for analyzing added phase noise across their whole operating bandwidth, based on a prior harmonic balance (HB) simulation and taking into account single transistor noise source models. Application of HB and Envelope-Transient simulation techniques to digital dividers is discussed. A 3&ndash;4 dual-modulus prescaler implemented in Source-Coupled FET Logic (SCFL) and manufactured in commercially available GaAs technology provides an example to illustrate the method. &copy; 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.
The Whole Story: Retrieving Narratives for Cross-Cultural Understanding
Authors: Alex Davis
Venue: Proceedings of the 3d International Conference on Online Communities and Social Computing: Held as Part of HCI International 2009 (2009)

We present a narrative-based approach to computer-mediated building of cross-cultural competence, and describe work on a case-based approach to the indexing and automated retrieval of culturally specific narratives. The narrative approach to culture reflects an anthropological view of the cross-cultural understanding problem, seeking understanding of cultural factors by creating computational representations of observed and reported narratives operant in various cultures, as well as narratives of cross-cultural interaction. These narratives constitute cases which can be retrieved using case-based reasoning, based on their applicability to a user's problem or environment, in a particular cultural context. The use of narrative in its original form has the advantage that it can be derived relatively intuitively from experts, literature, and historical record, and in addition to its direct suitability for gaining understanding, may be appropriate for adaptation to social media and simulation through automated agents.
A hybrid approach to convoy movement planning in an urban city
Authors: Ramesh Thangarajoo, Lucas Agussurja, Hoong Chuin Lau
Venue: Proceedings of the 20th national conference on Innovative applications of artificial intelligence - Volume 3 (2008)

In this paper, we consider a high-fidelity Convoy Movement Problem motivated by the coordination and routing of convoys within a road transportation network in an urban city. It encompasses two classical combinatorial optimization problems - vehicle routing and resource constrained scheduling. We present an effective hybrid algorithm to dynamically manage the movement of convoys, where we combine the standard Dijkstra's shortest-path algorithm with constraint programming techniques. The effectiveness of the algorithm is illustrated with testing on varying problem sizes and complexity.
Study of APT System for Laser Atmosphere Communication
Authors: Li Da-she, Nai Chang-xin, Hua Zhen
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

Using the laser transmission characteristic in atmosphere channel and request for APT, a new type of APT system is designed for real time communication. Work principles of each part are discussed in details. On the basis of a new idea of target locating and tracking algorithm, specifically flow and corresponding tracking algorithms is designed in order to accomplish the beam acquisition pointing and tracking. QD model is built for treatment method of error. So the system is viable.
A Study on Chaos in the Traffic Flow Based on the Coupled Map Model
Authors: Lijun Liu, Song Li
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

The chaos in the traffic flow based on couple map model is studied in this paper. The time series of the traffic flow are generated by using matlab program. The changing process of the space headway between the front and the following vehicle are obtained by the simulation. The influence of the model parameters on the movement of the traffic flow is discussed and the relevant simulation results are given. The analysis of the dynamic phase transitions in the traffic flow shows that the chaos exists in the traffic flow indeed, and the system passes to chaos following the Pomeau-Manneville scenario due to the variety of the model parameter.
Human Age Estimation by Metric Learning for Regression Problems
Authors: Leting Pan
Venue: Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (2009)

The estimation of human age from face images has many real-world applications. However, how to discover the intrinsic aging trend is still a challenging problem. We proposed a general distance metric learning scheme for regression problems, which utilizes not only data themselves, but also their corresponding labels to strengthen the credibility of distances. This metric could be learned by solving an optimization problem. Via the learned metric, it is easy to find the intrinsic variation trend of data by a relative small amount of samples without any prior knowledge of the structure or distribution of data. Furthermore, the test data could be projected to this metric by a simple linear transformation and it is easy to be combined with manifold learning algorithms to improve the performance. Experiments are conducted on the public FG-NET database by Gaussian process regression in the learned metric to validate our framework, which shows that its performance is improved over traditional regression methods.
Using integer linear programming for detecting speech disfluencies
Authors: Kallirroi Georgila
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers (2009)

We present a novel two-stage technique for detecting speech disfluencies based on Integer Linear Programming (ILP). In the first stage we use state-of-the-art models for speech disfluency detection, in particular, hidden-event language models, maximum entropy models and conditional random fields. During testing each model proposes possible disfluency labels which are then assessed in the presence of local and global constraints using ILP. Our experimental results show that by using ILP we can improve the performance of our models with negligible cost in processing time. The less training data is available the larger the improvement due to ILP.
Distinguishing Regional from Within-Codon Rate Heterogeneity in DNA Sequence Alignments
Authors: Alexander V. Mantzaris, Dirk Husmeier
Venue: Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics (2009)

We present an improved phylogenetic factorial hidden Markov model (FHMM) for detecting two types of mosaic structures in DNA sequence alignments, related to (1) recombination and (2) rate heterogeneity. The focus of the present work is on improving the modelling of the latter aspect. Earlier papers have modelled different degrees of rate heterogeneity with separate hidden states of the FHMM. This approach fails to appreciate the intrinsic difference between two types of rate heterogeneity: long-range regional effects, which are potentially related to differences in the selective pressure, and the short-term periodic patterns within the codons, which merely capture the signature of the genetic code. We propose an improved model that explicitly distinguishes between these two effects, and we assess its performance on a set of simulated DNA sequence alignments.
Harnessing accelerometer technology for inclusive mobile learning
Authors: Tracey J. Mehigan
Venue: Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services (2009)

The goal of this research is the establishment of a usable and accessible mobile learning system for the inclusion of both blind and vision-impaired students within mainstream education through independent, collaborative and ubiquitous mobile learning environments. An essential component of this work is the enhancement of the field to enable all students to work successfully together despite vision disabilities for the achievement of a learning outcome. Given the advancements in mobile technologies, and the personal nature of mobile devices, there is a lot to be gained, especially for the vision-impaired, by harnessing new technologies for education. Some technological advances can increase the divide between such students and their fully sighted peers. However the incorporation of technologies such as the accelerometer, now standard within many modern mobile phones, provides an opportunity to develop new inclusive mobile learning applications. The accelerometer could enable us to present a visionimpaired student with the capability to successfully play and interact directly with their fully sighted peers within a collaborative game to achieve a single outcome. This could be achieved without the heavy reliance on visual interfaces that were a necessary part of earlier mLearning models. The student would interact with the game through specific movements of their mobile handheld device. The device, for example, would be moved in one direction to give a specific command, while tilting and shaking the device would be used to command separate specific functions of the game. The student's interaction through the accelerometer could be enhanced through the provision of both haptic and audio feedback as they twist and tilt the handheld mobile device to interact with a learning game, removing altogether the need for the incorporation of a visual interface. The incorporation of wireless technologies such as Bluetooth, would allow for the provision of a collaborative environment for mobile learning, allowing all students to communicate via their handheld device, regardless of the disabilities faced by individual learners. Providing the ability to create an engaging, level playing field for such students could reduce the digital divide currently in existence for the future success of mobile learning environments.
Evaluating the Influence of Roads on Land Ecological Security Using GIS - A Case Study in Hengshan County
Authors: Liu Shiliang, Dong Yuhong
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

As widespread features of landscape and human disturbance paths, road networks bring forth many ecological effects and affect the regional land ecological security. In this paper, the methods of GIS buffer were used to elucidate the influence of roads on landscape and assess the road impacts on land ecological security in Hengshan county. Land use change greatly with different buffers. Landscape fragmentation (Ci), landscape division (Ai), landscape dominance (D) in 500m buffer zone differed greatly between different land uses. Then based on different ecological effects on pattern and process, we put forward ecological security index of pattern and process, then comprehensively assessed various potential and accumulative ecological effects of road networks. The results indicated that though ecological security distributed differently in each town area, the road density had high negative linear relationship with the security levels.
A Comparison of Feature Detectors with Passive and Task-Based Visual Saliency
Authors: Patrick Harding, Neil M. Robertson
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

This paper investigates the coincidence between six interest point detection methods (SIFT, MSER, Harris-Laplace, SURF, FAST Kadir-Brady Saliency) with two robust "bottom-up" models of visual saliency (Itti and Harel) as well as "task" salient surfaces derived from observer eye-tracking data. Comprehensive statistics for all detectors vs. saliency models are presented in the presence and absence of a visual search task. It is found that SURF interest-points generate the highest coincidence with saliency and the overlap is superior by 15% for the SURF detector compared to other features. The overlap of image features with task saliency is found to be also distributed towards the salient regions. However the introduction of a specific search task creates high ambiguity in knowing how attention is shifted. It is found that the Kadir-Brady interest point is more resilient to this shift but is the least coincident overall.