Predicting ConceptNet Path Quality Using Crowdsourced Assessments of Naturalness

In many applications, it is important to characterize the way in which two concepts are semantically related. Knowledge graphs such as ConceptNet provide a rich source of information for such characterizations by encoding relations between concepts as edges in a graph. When two concepts are not directly connected by an edge, their relationship can still be described in terms of the paths that connect them. Unfortunately, many of these paths are uninformative and noisy, which means that the success of applications that use such path features crucially relies on their ability to select high-quality paths. In existing applications, this path selection process is based on relatively simple heuristics. In this paper we instead propose to learn to predict path quality from crowdsourced human assessments. Since we are interested in a generic task-independent notion of quality, we simply ask human participants to rank paths according to their subjective assessment of the paths' naturalness, without attempting to define naturalness or steering the participants towards particular indicators of quality. We show that a neural network model trained on these assessments is able to predict human judgments on unseen paths with near optimal performance. Most notably, we find that the resulting path selection method is substantially better than the current heuristic approaches at identifying meaningful paths.Comment: In Proceedings of the Web Conference (WWW) 201

Path Quality Estimator for 802.15.4e TSCH Fast Deployment Tool

[EN] This paper introduces a novel quality estimator that uses different metrics to decide the best path towards the root in Wireless Sensor Networks. The different metrics are assessed at medium access control layer (MAC), under the IEEE 802.15.4 standard, and are used at network layer, enhancing the best path selection process done by the routing protocol, and at the application layer, enabling visual quality indicators in the nodes. This quality function is used during deployment stage; ensuring nodes are located optimally and nimbly. This mechanism will help WSN¿s adoption in Industrial Internet of Things applications.This work is supported by IVACE (Insituto Valenciano de Competitividad Empresarial) through FEDER funding (exp. IMDEEA/2017/103).Vera-Pérez, J.; Todoli Ferrandis, D.; Santonja Climent, S.; Silvestre-Blanes, J.; Sempere Paya, VM. (2018). Path Quality Estimator for 802.15.4e TSCH Fast Deployment Tool. Telfor Journal (Online). 10(1):2-7. https://doi.org/10.5937/telfor1801002VS27101O. Gaddour, A. Koubâa, S. Chaudhry, M. Tezeghdanti, R. Chaari and M. Abid, 'Simulation and Performance Evaluation of DAG Construction with RPL,' in IEEE Third International Conference on Communications and Networking (ComNet), pp. 1-8, 2012.;IETF, 'RFC 6552 - Objective Function Zero for the Routing Protocol for Low-Power and Lossy Networks (RPL),' 2012.;IETF, 'RFC 6719 - The Minimum Rank with Hysteresis Objective Function,' 2012.;N. Pradeska, Widyawan, W. Najib and S. S. Kusumawardani, 'Performance Analysis of Objective Function MRHOF and OF0 in Routing Protocol RPL IPv6 Over Low Power Wireless Personal Area Networks (6LoWPAN),' in 8th International Conference on Information Technology and Electrical Engineering (ICITEE), Yogyakarta, Indonesia, 2016.;P. O. Kamgueu, E. Nataf, T. D. Ndié and O. Festor, 'Energy-based routing metric for RPL,' Doctoral dissertation, INRIA, 2013.;H.-S. Kim, J. Paek and S. Bahk, 'QU-RPL: Queue utilization based RPL for load balancing in large scale industrial applications,' in 12th Annual IEEE International Conference on Sensing, Communication and Networking (SECON), Seattle, WA, USA, 2015.;P. Gonizzi, R. Monica and G. Ferrari, 'Design and evaluation of a delay-efficient RPL routing metric,' in 9th International Wireless Communication and Mobile Computing Conference (IWCMC), Sardinia, Italy, 2013.;IETF, 'RFC 6551 - Routing Metrics Used for Path Calculation in Low-Power and Lossy Networks,' 2012.;N. Baccour, A. Koubâa, L. Mottola, M. A. Zúñiga, H. Youssef, C. A. Boano and M. Alves, 'Radio link quality estimation in wireless sensor networks: A survey,' ACM Transactions on Sensor Networks (TOSN), vol. 8 (4), 2012.;P. Karkazis, H. C. Leligou, L. Sarakis, T. Zahariadis, P. Trakadas, T. H. Velivassaki and C. Capsalis, 'Design of primary and composite routing metrics for RPL-compliant Wireless Sensor Networks,' in International Conference on Telecommunications and Multimedia (TEMU), Chania, Greece, 2012.;N. Baccour, A. Koubâa, H. Youssef, M. B. Jamâa, D. d. Rosário, M. Alves and L. B. Becker, 'F-LQE: A Fuzzy Link Quality Estimator for Wireless Sensor Networks,' in European Conference on Wireless Sensor Networks (EWSN), Coimbra, Portugal, 2010.;S. Rekik, N. Baccour, M. Jmaiel and K. Drira, 'Holistic link quality estimation-based routing metric for RPL networks in smart grids,' in IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Valencia, Spain, 2016.;O. Gaddour, A. Koubaa, N. Baccour and M. Abid, 'OF-FL: QoSaware fuzzy logic objective function for the RPL routing protocol,' in 12th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), Hammamet, Tunisia, 2014.;IETF, 'RFC 8180 - Minimal IPv6 over TSCH Mode of IEEE 802.15.4e (6TiSCH) Configuration,' 2017.;M. G. Amor, A. Koubâa, E. Tovar and M. Khalgui, 'Cyber-OF: An Adaptative Cyber-Physical Objective Function for Smart Cities Applications,' in 28th Euromicro Conference on Real-Time Systems (ECRTS), Toulouse, France, 2016.;J. Vera-Pérez, D. Todolí-Ferrandis, J. Silvestre-Blanes, S. SantonjaCliment and V. Sempere-Paya, 'Path quality estimator for wireless sensor networks fast deployment tool,' 2017 25th Telecommunication Forum (TELFOR), Belgrade, 2017, pp. 1-4.

Farthest Greedy Path Sampling for Two-shot Recommender Search

Weight-sharing Neural Architecture Search (WS-NAS) provides an efficient mechanism for developing end-to-end deep recommender models. However, in complex search spaces, distinguishing between superior and inferior architectures (or paths) is challenging. This challenge is compounded by the limited coverage of the supernet and the co-adaptation of subnet weights, which restricts the exploration and exploitation capabilities inherent to weight-sharing mechanisms. To address these challenges, we introduce Farthest Greedy Path Sampling (FGPS), a new path sampling strategy that balances path quality and diversity. FGPS enhances path diversity to facilitate more comprehensive supernet exploration, while emphasizing path quality to ensure the effective identification and utilization of promising architectures. By incorporating FGPS into a Two-shot NAS (TS-NAS) framework, we derive high-performance architectures. Evaluations on three Click-Through Rate (CTR) prediction benchmarks demonstrate that our approach consistently achieves superior results, outperforming both manually designed and most NAS-based models.Comment: 9 pages, 5 figure

Enhancing the Transition-based RRT to deal with complex cost spaces

The Transition-based RRT (T-RRT) algorithm enables to solve motion planning problems involving configuration spaces over which cost functions are defined, or cost spaces for short. T-RRT has been successfully applied to diverse problems in robotics and structural biology. In this paper, we aim at enhancing T-RRT to solve ever more difficult problems involving larger and more complex cost spaces. We compare several variants of T-RRT by evaluating them on various motion planning problems involving different types of cost functions and different levels of geometrical complexity. First, we explain why applying as such classical extensions of RRT to T-RRT is not helpful, both in a mono-directional and in a bidirectional context. Then, we propose an efficient Bidirectional T-RRT, based on a bidirectional scheme tailored to cost spaces. Finally, we illustrate the new possibilities offered by the Bidirectional T-RRT on an industrial inspection problem

Корреляционный параметр качества аддитивного маскирования речевых сигналов

Розглянута методика цифрової кореляційної обробки контрольного фрагменту мови, що дозволяє на основі розрахунку коефіцієнта кореляції обґрунтувати аналітичну оцінку параметра якості передачі сигналу мови каналами зв’язку та проводити аналіз ефективності адитивного маскування мовних сигналів.The method of check utterance digital correlation processing, which allows to substantiate the communication path quality criteria analytic estimation on the base of correlation coefficient calculation and to analyze the speech signal additive masking effectiveness is under review

Анализ результатов артикуляционных и сегментальных испытаний сигналов маскирования речи

Розглянуто методику та результати випробувань цифрової кореляційної обробки контрольного фрагменту мови, що дозволяє на основі розрахунку коефіцієнта кореляції обґрунтувати аналітичну оцінку параметра якості передачі сигналу мови каналами зв’язку та проводити аналіз ефективності адитивного маскування мовних сигналів.The method of check utterance digital correlation processing, which allows to substantiate the communication path quality criteria analytic estimation on the base of correlation coefficient calculation and to analyze the speech signal additive masking effectiveness is under review

RMPD - A Recursive Mid-Point Displacement Algorithm for Path Planning

Motivated by what is required for real-time path planning, the paper starts out by presenting sRMPD, a new recursive "local" planner founded on the key notion that, unless made necessary by an obstacle, there must be no deviation from the shortest path between any two points, which would normally be a straight line path in the configuration space. Subsequently, we increase the power of sRMPD by using it as a "connect" subroutine call in a higher-level sampling-based algorithm mRMPD that is inspired by multi-RRT. As a consequence, mRMPD spawns a larger number of space exploring trees in regions of the configuration space that are characterized by a higher density of obstacles. The overall effect is a hybrid tree growing strategy with a trade-off between random exploration as made possible by multi-RRT based logic and immediate exploitation of opportunities to connect two states as made possible by sRMPD. The mRMPD planner can be biased with regard to this trade-off for solving different kinds of planning problems efficiently. Based on the test cases we have run, our experiments show that mRMPD can reduce planning time by up to 80% compared to basic RRT