ppxscal/embedding_network huggingface dataset:
Social ranking: uncovering relevant content using tag-based recommender systems
Authors: Valentina Zanardi, Licia Capra
Venue: Proceedings of the 2008 ACM conference on Recommender systems (2008)

Social (or folksonomic) tagging has become a very popular way to describe, categorise, search, discover and navigate content within Web 2.0 websites. Unlike taxonomies, which overimpose a hierarchical categorisation of content, folksonomies empower end users by enabling them to freely create and choose the categories (in this case, tags) that best describe some content. However, as tags are informally defined, continually changing, and ungoverned, social tagging has often been criticised for lowering, rather than increasing, the efficiency of searching, due to the number of synonyms, homonyms, polysemy, as well as the heterogeneity of users and the noise they introduce. In this paper, we propose Social Ranking, a method that exploits recommender system techniques to increase the efficiency of searches within Web 2.0. We measure users' similarity based on their past tag activity. We infer tags' relationships based on their association to content. We then propose a mechanism to answer a user's query that ranks (recommends) content based on the inferred semantic distance of the query to the tags associated to such content, weighted by the similarity of the querying user to the users who created those tags. A thorough evaluation conducted on the CiteULike dataset demonstrates that Social Ranking neatly improves coverage, while not compromising on accuracy.
Seasonal reflectance course of some forest types in Estonia from a series of Landsat TM and SPOT images and via simulation
Authors: T. Nilson, S. Suviste, T. Lukk, A. Eenmae
Venue: International Journal of Remote Sensing (2008)

A time series of Landsat TM and SPOT images over the Jarvselja forest region of southeast Estonia was compiled from a set of 23 images acquired in the years 1986 to 2003 in order to study the seasonal changes in reflectance among different forest types. The images were transformed into ground-level reflectance factor units and seasonal courses of reflectance were constructed for several forest types in all six reflective spectral bands of Landsat TM. For better comparability between different years, the seasonal time course was presented as a function of temperature (phenology) time. A smoothing of the time series was also applied. The smoothed seasonal series were compared with model simulations for the same forest types using the Kuusk-Nilson forest reflectance model. The input for the model was formed using the data from the respective forestry database. An expert estimate was used to obtain the values for the biochemical and biophysical parameters lacking in the forestry database and of their change in course in the season. The simulations showed that, as main driving factors in the seasonal course, the course of leaf area index (LAI) of overstorey and understorey, chlorophyll content in leaves and ground wetness could be pointed out. The course of sun elevation during the season appeared also to be important in forming the image-based seasonal course. For the studied forest types, the seasonal average normalised difference vegetation index (NDVI) was calculated from the smoothed seasonal courses of reflectance in the red and near infrared bands. The validity of the Monteith hypothesis was tested by establishing a linear relation between the yearly trunk mass increment and seasonal average NDVI.
Category Classification and Topic Discovery of Japanese and English News Articles
Authors: David B. Bracewell, Jiajun Yan, Fuji Ren, Shingo Kuroiwa
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

This paper presents algorithms for topic analysis of news articles. Topic analysis entails category classification and topic discovery and classification. Dealing with news has special requirements that standard classification approaches typically cannot handle. The algorithms proposed in this paper are able to do online training for both category and topic classification as well as discover new topics as they arise. Both algorithms are based on a keyword extraction algorithm that is applicable to any language that has basic morphological analysis tools. As such, both the category classification and topic discovery and classification algorithms can be easily used by multiple languages. Through experimentation the algorithms are shown to have high precision and recall in tests on English and Japanese.
Social Tagging Behaviour in Community-Driven Question Answering
Authors: Eduarda Mendes Rodrigues, Natasa Milic-Frayling, Blaz Fortuna
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01 (2008)

On-line community services such as Live QnA and Yahoo! Answers enable their members to ask questions and have them answered by the community. The questions are labelled by the users to facilitate search, navigation, and recommendations. In this paper we provide an in-depth analysis of the question labelling practices by contrasting the use of community generated tags in the Live QnA service with the use of topic categories from a fixed taxonomy in the Yahoo! Answers service. We found that community tagging is related to higher levels of social interactions amongst users. Analysis of the most frequently used community tags reveals that active users may establish strong social ties around specific tags. Furthermore, the discriminative value of individual community tags can be low since the corresponding questions may cover a variety of topics. Thus, appropriate care needs to be taken when designing search, browsing, and recommender features for question discovery.
Out-of-order processing: a new architecture for high-performance stream systems
Authors: Jin Li, Kristin Tufte, Vladislav Shkapenyuk, Vassilis Papadimos, Theodore Johnson, David Maier
Venue: Proceedings of the VLDB Endowment (2008)

Many stream-processing systems enforce an order on data streams during query evaluation to help unblock blocking operators and purge state from stateful operators. Such in-order processing (IOP) systems not only must enforce order on input streams, but also require that query operators preserve order. This order-preserving requirement constrains the implementation of stream systems and incurs significant performance penalties, particularly for memory consumption. Especially for high-performance, potentially distributed stream systems, the cost of enforcing order can be prohibitive. We introduce a new architecture for stream systems, out-of-order processing (OOP), that avoids ordering constraints. The OOP architecture frees stream systems from the burden of order maintenance by using explicit stream progress indicators, such as punctuation or heartbeats, to unblock and purge operators. We describe the implementation of OOP stream systems and discuss the benefits of this architecture in depth. For example, the OOP approach has proven useful for smoothing workload bursts caused by expensive end-of-window operations, which can overwhelm internal communication paths in IOP approaches. We have implemented OOP in two stream systems, Gigascope and NiagaraST. Our experimental study shows that the OOP approach can significantly outperform IOP in a number of aspects, including memory, throughput and latency.
Automated identification of parameter mismatches in web applications
Authors: William G. J. Halfond, Alessandro Orso
Venue: Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering (2008)

Quality assurance techniques for web applications have become increasingly important as web applications have gained in popularity and become an essential part of our daily lives. To integrate content and data from multiple sources, the components of a web application communicate extensively among themselves. Unlike traditional program modules, the components communicate through interfaces and invocations that are not explicitly declared. Because of this, the communication between two components can fail due to a parameter mismatch between the interface invoked by a calling component and the interface provided by the called component. Parameter mismatches can cause serious errors in the web application and are difficult to identify using traditional testing and verification techniques. To address this problem, we propose a static-analysis based approach for identifying parameter mismatches. We also present an empirical evaluation of the approach, which we performed on a set of real web applications. The results of the evaluation are promising; our approach discovered 133 parameter mismatches in the subject applications.
Coding of checksum components for increasing the control reliability of data transmission for military applications
Authors: Nikolaos Bardis
Venue: WSEAS Transactions on Information Science and Applications (2008)

Computer Systems used in Military and other challenging applications, are often exposed to increased levels of electromagnetic radiation. Embedded systems falling in this category often suffer from this exposure due to the operation of the device to which they belong. Consequently data communications within such devices need to be protected against transmission errors. Current general purpose encoding schemes that are used in other communication applications are prohibitively complex for this application. In this paper an innovative extension to the well known checksum concept is proposed that is capable of controlling errors in intra device data transfers. The new technique is shown to be simple enough for implementation and to increase the probability of detection of errors by several orders of magnitude. The scheme is hence shown to be suitable for embedded computing platforms for military and other demanding systems. More specifically, the modified checksum is examined in respect of its suitability for use in schemes for the transient error detection in schemes for reliable data storage within computing systems and it is explained why it is extremely suitable for this application. The modified checksum is also considered in the context of algorithm based fault tolerance schemes and it is again concluded that it can contribute to the overall scheme efficiency and effectiveness. The modified checksum is hence shown to be an algorithmic tool that can significantly contribute to the design of reliable and fault tolerant computing systems, such as the ones used for military systems or other applications that operate in adverse environments.
Quasi-invariant control: Design and functional capabilities
Authors: Yu. I. Neimark
Venue: Automation and Remote Control (2008)

The questions of physical realizability, stability, and control errors were considered by the example of a simplest mathematical model of the linear minimum phase system of quasi-invariant control. The problem of designing the quasi-invariant control was solved on this basis, thus providing the opportunity to extend control by designing a nonlinear system combining the quasi-invariant and classical control strategies.
LeeWave: level-wise distribution of wavelet coefficients for processing kNN queries over distributed streams
Authors: Mi-Yen Yeh, Kun-Lung Wu, Philip S. Yu, Ming-Syan Chen
Venue: Proceedings of the VLDB Endowment (2008)

We present LeeWave --- a bandwidth-efficient approach to searching range-specified k-nearest neighbors among distributed streams by LEvEl-wise distribution of WAVElet coefficients. To find the k most similar streams to a range-specified reference one, the relevant wavelet coefficients of the reference stream can be sent to the peer sites to compute the similarities. However, bandwidth can be unnecessarily wasted if the entire relevant coefficients are sent simultaneously. Instead, we present a level-wise approach by leveraging the multi-resolution property of the wavelet coefficients. Starting from the top and moving down one level at a time, the query initiator sends only the single-level coefficients to a progressively shrinking set of candidates. However, there is one difficult challenge in LeeWave: how does the query initiator prune the candidates without knowing all the relevant coefficients? To overcome this challenge, we derive and maintain a similarity range for each candidate and gradually tighten the bounds of this range as we move from one level to the next. The increasingly tightened similarity ranges enable the query initiator to effectively prune the candidates without causing any false dismissal. Extensive experiments with real and synthetic data show that, when compared with prior approaches, LeeWave uses significantly less bandwidth under a wide range of conditions.
How changes in context affect human behaviours and performance in mobile computing systems
Authors: Yong Jun Choi
Venue: WSEAS Transactions on Systems and Control (2008)

Many real world mobile device interactions occur in context-rich environment. Information about how users react to changes in context and perform in context-rich environments is crucial to informing strategies for mobile device design. Thus, the context of use must be considered because there are multiple tasks taking place in many mobile computing interactions. However, few empirical studies on mobile computing regarding changes in context impact users' abilities to perform effectively are conducted to date. In this investigation, context is presumed to be a set of conditions or user states that influence the ways in which a human interacts with a mobile computing device. In order to sense and record relevant contextual factors, the investigations have been conducted to enable a device to sense characteristics of mobility, such as motion and changes in environmental conditions like lighting. The result indicates that the way in which users' behaviour is affected by changes in context is not uniform.
Context-based recognition during human interactions: automatic feature selection and encoding dictionary
Authors: Louis-Philippe Morency, Iwan de Kok, Jonathan Gratch
Venue: Proceedings of the 10th international conference on Multimodal interfaces (2008)

During face-to-face conversation, people use visual feedback such as head nods to communicate relevant information and to synchronize rhythm between participants. In this paper we describe how contextual information from other participants can be used to predict visual feedback and improve recognition of head gestures in human-human interactions. For example, in a dyadic interaction, the speaker contextual cues such as gaze shifts or changes in prosody will influence listener backchannel feedback (e.g., head nod). To automatically learn how to integrate this contextual information into the listener gesture recognition framework, this paper addresses two main challenges: optimal feature representation using an encoding dictionary and automatic selection of optimal feature-encoding pairs. Multimodal integration between context and visual observations is performed using a discriminative sequential model (Latent-Dynamic Conditional Random Fields) trained on previous interactions. In our experiments involving 38 storytelling dyads, our context-based recognizer significantly improved head gesture recognition performance over a vision-only recognizer.
IGlasses: an automatic wearable speech supplementin face-to-face communication and classroom situations
Authors: Dominic W. Massaro, Miguel Á Carreira-Perpiñán, David J. Merrill, Cass Sterling, Stephanie Bigler, Elise Piazza, Marcus Perlman
Venue: Proceedings of the 10th international conference on Multimodal interfaces (2008)

The need for language aids is pervasive in today's world. There are millions of individuals who have language and speech challenges, and these individuals require additional support for communication and language learning. We demonstrate technology to supplement common face-to-face language interaction to enhance intelligibility, understanding, and communication, particularly for those with hearing impairments. Our research is investigating how to automatically supplement talking faces with information that is ordinarily conveyed by auditory means. This research consists of two areas of inquiry: 1) developing a neural network to perform real-time analysis of selected acoustic features for visual display, and 2) determining how quickly participants can learn to use these selected cues and how much they benefit from them when combined with speechreading.
Public key cryptography based privacy preserving multi-context RFID infrastructure
Authors: Selim Volkan Kaya, Erkay Savaş, Albert Levi, Özgür Erçetin
Venue: Ad Hoc Networks (2009)

In this paper, we propose a novel radio frequency identification (RFID) infrastructure enabling multi-purpose RFID tags realized by the use of privacy preserving public key cryptography (PKC) architecture. The infrastructure ensures that the access rights of the tags are preserved based on the spatial and temporal information collected from the RFID readers. We demonstrate that the proposed scheme is secure with respect to cryptanalytic, impersonation, tracking, replay, and relay attacks. We also analyze the feasibility of PKC implementation on passive class 2 RFID tags, and show that the requirements for PKC are comparable to those of other cryptographic implementations based on symmetric ciphers. Our numerical results indicate PKC based systems can outperform symmetric cipher based systems, since the back end servers can identify RFID tags with PKC based systems approximately 57 times faster than the best symmetric cipher based systems.
The discrete multidimensional MPUM
Authors: Eva Zerz
Venue: Multidimensional Systems and Signal Processing (2008)

Given a finite set of polynomial-exponential, multivariate, and vector-valued sequences, we show how the smallest linear shift-invariant set containing the data trajectories can be written as the solution set of a system of linear difference equations with constant coefficients. The resulting representation is known as the most powerful unfalsified model (MPUM) in behavioral systems theory. We address the case where the components of the given sequences take their values in a field, as well as the case where these values belong to a finite ring of the form $${{\mathbb{Z}}/m{\mathbb{Z}}}$$ for an integer m > 1.
The use of parabolic arcs in matching curved boundaries by point transformations for some higher order triangular elements
Authors: H. T. Rathod, K. V. Nagaraja, V. Kesavulu Naidu, B. Venkatesudu
Venue: Finite Elements in Analysis and Design (2008)

This paper is concerned with curved boundary triangular elements having one curved side and two straight sides. The curved elements considered here are the 6-node (quadratic), 10-node (cubic), 15-node (quartic) and 21-node (quintic) triangular elements. On using the isoparametric coordinate transformation, these curved triangles in the global (x,y) coordinate system are mapped into a standard triangle: {(@x,@h)/0=
Using VSI EWMA charts to monitor dependent process steps with incorrect adjustment
Authors: Su-Fen Yang, Yi-Ning Yu
Venue: Expert Systems with Applications: An International Journal (2009)

The article considers the variable process control scheme for two dependent process steps with incorrect adjustment. Incorrect adjustment of a process may result in shifts in process mean, ultimately affecting the quality of products. We construct variable sampling interval (VSI) EWMA"Z"""X and EWMA"Z"""e control charts to effectively monitor the quality variable produced by the first process step with incorrect adjustment and the quality variable produced by the second process step with incorrect adjustment. The performance of the proposed VSI control charts is measured by the adjusted average time to signal (AATS) derived using a Markov chain approach. An example of the automobile braking system with incorrect adjustment shows the application and performance of the proposed VSI EWMA"Z"""X and EWMA"Z"""e control charts in detecting shifts in process mean. Furthermore, the performance of the proposed VSI EWMA"Z"""X and EWMA"Z"""e control charts and the fixed sampling interval (FSI) EWMA"Z"""X and EWMA"Z"""e control charts are compared by numerical analysis results. These demonstrate that the former is much faster in detecting small and median shifts in mean. The optimum VSI EWMA"Z"""X and EWMA"Z"""e control charts are also proposed using optimization technique to minimize AATS when quality engineers cannot specify the values of variable sampling intervals. It has been found that the optimum VSI EWMA"Z"""X and EWMA"Z"""e control charts always work better than the VSI EWMA"Z"""X and EWMA"Z"""e control charts.
Competitive analysis of online traffic grooming in WDM rings
Authors: Karyn Benson, Benjamin Birnbaum, Esteban Molina-Estolano, Ran Libeskind-Hadas
Venue: IEEE/ACM Transactions on Networking (TON) (2008)

This paper addresses the problem of traffic grooming in wavelength-division multiplexing (WDM) rings where connection requests arrive online. Each request specifies a pair of nodes that wish to communicate and also the desired bandwidth of this connection. If the request is to be satisfied, it must be allocated to one or more wavelengths with sufficient remaining capacity. We consider three distinct profit models specifying the profit associated with satisfying a connection request. We give results on offline and online algorithms for each of the three profit models. We use the paradigm of competitive analysis to theoretically analyze the quality of our online algorithms. Finally, experimental results are given to provide insight into the performance of these algorithms in practice.
Pfp: parallel fp-growth for query recommendation
Authors: Haoyuan Li, Yi Wang, Dong Zhang, Ming Zhang, Edward Y. Chang
Venue: Proceedings of the 2008 ACM conference on Recommender systems (2008)

Frequent itemset mining (FIM) is a useful tool for discovering frequently co-occurrent items. Since its inception, a number of significant FIM algorithms have been developed to speed up mining performance. Unfortunately, when the dataset size is huge, both the memory use and computational cost can still be prohibitively expensive. In this work, we propose to parallelize the FP-Growth algorithm (we call our parallel algorithm PFP) on distributed machines. PFP partitions computation in such a way that each machine executes an independent group of mining tasks. Such partitioning eliminates computational dependencies between machines, and thereby communication between them. Through empirical study on a large dataset of 802,939 Web pages and 1,021,107 tags, we demonstrate that PFP can achieve virtually linear speedup. Besides scalability, the empirical study demonstrates that PFP to be promising for supporting query recommendation for search engines.
CCMAC: coordinated cooperative MAC for wireless LANs
Authors: Zhengqing Hu, Chen-Khong Tham
Venue: Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems (2008)

In wireless LANs, one of the main concerns is throughput performance. When there is only one Access Point (AP) in a wireless LAN, the bottleneck is normally at the region near the AP. In this paper, we propose CCMAC, a coordinated cooperative MAC for wireless LANs. It is designed to improve the throughput performance in the region near the AP through cooperative communication, where data is forwarded through a two-hop high data-rate link instead of a low data-rate direct link. Furthermore, it can coordinate nodes to perform concurrent transmissions in order to further increase throughput. This coordination is done by modeling the problem as a POMDP (Partially Observable Markov Decision Process) and using a Reinforcement Learning (RL) algorithm to solve it. Through analysis and simulation, we show that CCMAC can significantly shorten the transmission time for stations with low data rate links to the AP and it has better throughput performance than other MAC protocols, such as CoopMAC and legacy IEEE 802.11.