scholarly journals Exploiting geotagged resources to spatial ranking by extending HITS algorithm

2015 ◽  
Vol 12 (1) ◽  
pp. 185-201 ◽  
Author(s):  
Nguyen Tri ◽  
Jason Jung
Keyword(s):  
Location Based Services ◽  
Experimental Results ◽  
Smart Devices ◽  
Ranking Algorithm ◽  
Weighting Schemes ◽  
Novel Method ◽  
Meaningful Relationships ◽  
Spatial Ranking ◽  
Hits Algorithm ◽  
Font Color

With a large amount of geotagged resources from smart devices, it is important to provide users with intelligent location-based services. Particularly, in this work, we focus on spatial ranking service, which can retrieve a set of relevant resources with a certain tag. This paper designs ranking algorithm in order to find out a list of locations which are collected from geotagged resources on SNSs. As extending HITS algorithm [13], we propose a novel method (called GeoHITS) that can analyze an undirected 2-mode graph composed with a set of tags and a set of locations. Thereby, meaningful relationships between the locations and a set of tags are discovered by integrating several weighting schemes and HITS algorithm. To evaluate the proposed spatial ranking approach, we have shows the experimental results from the recommendation applications. <br><br><font color="red"><b> This article has been corrected. Link to the correction <u><a href="http://dx.doi.org/10.2298/CSIS151203064E">10.2298/CSIS151203064E</a><u></b></font>

scholarly journals Hybrid Indoor Localization Using WiFi and UWB Technologies

Electronics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 334 ◽  
Author(s):  
Stefania Monica ◽  
Federico Bergenti
Keyword(s):  
Indoor Localization ◽  
Sufficient Accuracy ◽  
Location Based Services ◽  
Experimental Results ◽  
Smart Devices ◽  
Major Drawback ◽  
Wireless Technologies ◽  
Hybrid Approaches ◽  
Accurate Localization

The interest in indoor localization has been increasing in the last few years because of the numerous important applications related to the pervasive diffusion of mobile smart devices that could benefit from localization. Various wireless technologies are in use to perform indoor localization, and, among them, WiFi and UWB technologies are appreciated when robust and accurate localization is required. The major advantage of WiFi technology is that it is ubiquitous, and therefore it can be used to support localization without the introduction of a specific infrastructure. The major drawback of WiFi technology is that it does not often ensure sufficient accuracy. On the contrary, indoor localization based on UWB technology guarantees higher accuracy with increased robustness, but it requires the use of UWB-enabled devices and the deployment of specific infrastructures made of UWB beacons. Experimental results on the synergic use of WiFi and UWB technologies for localization are presented in this paper to show that hybrid approaches can be used to effectively to increase the accuracy of WiFi-based localization. Actually, presented experimental results show that the use of a small number of UWB beacons together with an ordinary WiFi infrastructure is sufficient to significantly increase the accuracy of localization and to make WiFi-based localization adequate to implement relevant location-based services and applications.

scholarly journals Erratum to: Exploiting geotagged resources to spatial ranking by extending hits algorithm

2016 ◽  
Vol 13 (1) ◽  
pp. 309-309
Author(s):  
E Editorial
Keyword(s):  
Spatial Ranking ◽  
Hits Algorithm ◽  
Font Color

This article (Vol. 12, No. 1, pp. 185-201, 2015) was published with an error in the affiliation of the second author. The correct affiliations of the second author are "Yeungnam University" and "Chung-Ang Univeresity" as shown in this erratum note. <br><br><font color="red"><b> Link to the corrected article <u><a href="http://dx.doi.org/10.2298/CSIS141015091T">10.2298/CSIS141015091T</a></b></u>

scholarly journals Evaluation of Multi-Sensor Fusion Methods for Ultrasonic Indoor Positioning

2021 ◽  
Vol 11 (15) ◽  
pp. 6805
Author(s):  
Khaoula Mannay ◽  
Jesús Ureña ◽  
Álvaro Hernández ◽  
José M. Villadangos ◽  
Mohsen Machhout ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Experimental Tests ◽  
Indoor Positioning ◽  
Location Based Services ◽  
Smart Devices ◽  
Final Position ◽  
Positioning Systems ◽  
Local Positioning System ◽  
Tightly Coupled ◽  
Position Estimate

Indoor positioning systems have become a feasible solution for the current development of multiple location-based services and applications. They often consist of deploying a certain set of beacons in the environment to create a coverage volume, wherein some receivers, such as robots, drones or smart devices, can move while estimating their own position. Their final accuracy and performance mainly depend on several factors: the workspace size and its nature, the technologies involved (Wi-Fi, ultrasound, light, RF), etc. This work evaluates a 3D ultrasonic local positioning system (3D-ULPS) based on three independent ULPSs installed at specific positions to cover almost all the workspace and position mobile ultrasonic receivers in the environment. Because the proposal deals with numerous ultrasonic emitters, it is possible to determine different time differences of arrival (TDOA) between them and the receiver. In that context, the selection of a suitable fusion method to merge all this information into a final position estimate is a key aspect of the proposal. A linear Kalman filter (LKF) and an adaptive Kalman filter (AKF) are proposed in that regard for a loosely coupled approach, where the positions obtained from each ULPS are merged together. On the other hand, as a tightly coupled method, an extended Kalman filter (EKF) is also applied to merge the raw measurements from all the ULPSs into a final position estimate. Simulations and experimental tests were carried out and validated both approaches, thus providing average errors in the centimetre range for the EKF version, in contrast to errors up to the meter range from the independent (not merged) ULPSs.

scholarly journals Privacy Leakage in Mobile Sensing: Your Unlock Passwords Can Be Leaked through Wireless Hotspot Functionality

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Jie Zhang ◽  
Xiaolong Zheng ◽  
Zhanyong Tang ◽  
Tianzhang Xing ◽  
Xiaojiang Chen ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Mobile Sensing ◽  
Experimental Results ◽  
Smart Devices ◽  
Detection Accuracy ◽  
Phase Information ◽  
Current Sensing ◽  
Privacy Leakage ◽  
Sensing Systems ◽  
Additional Hardware

Mobile sensing has become a new style of applications and most of the smart devices are equipped with varieties of sensors or functionalities to enhance sensing capabilities. Current sensing systems concentrate on how to enhance sensing capabilities; however, the sensors or functionalities may lead to the leakage of users’ privacy. In this paper, we present WiPass, a way to leverage the wireless hotspot functionality on the smart devices to snoop the unlock passwords/patterns without the support of additional hardware. The attacker can “see” your unlock passwords/patterns even one meter away. WiPass leverages the impacts of finger motions on the wireless signals during the unlocking period to analyze the passwords/patterns. To practically implement WiPass, we are facing the difficult feature extraction and complex unlock passwords matching, making the analysis of the finger motions challenging. To conquer the challenges, we use DCASW to extract feature and hierarchical DTW to do unlock passwords matching. Besides, the combination of amplitude and phase information is used to accurately recognize the passwords/patterns. We implement a prototype of WiPass and evaluate its performance under various environments. The experimental results show that WiPass achieves the detection accuracy of 85.6% and 74.7% for passwords/patterns detection in LOS and in NLOS scenarios, respectively.

Web Page Ranking Algorithm Based on the Meta-Information

2014 ◽  
Vol 596 ◽  
pp. 292-296
Author(s):  
Xin Li Li
Keyword(s):  
Experimental Results ◽  
High Rank ◽  
Ranking Algorithm ◽  
Web Page ◽  
Page Ranking ◽  
Two Factors ◽  
Meta Information ◽  
The Web

PageRank algorithms only consider hyperlink information, without other page information such as page hits frequency, page update time and web page category. Therefore, the algorithms rank a lot of advertising pages and old pages pretty high and can’t meet the users' needs. This paper further studies the page meta-information such as category, page hits frequency and page update time. The Web page with high hits frequency and with smaller age should get a high rank, while the above two factors are more or less dependent on page category. Experimental results show that the algorithm has good results.

scholarly journals Obstacle Detection in Cluttered Traffic Environment Based on Candidate Generation and Classification

2006 ◽  
Vol 1 (4) ◽  
pp. 93 ◽  
Author(s):  
Qing Li ◽  
F.C. Sun
Keyword(s):  
Vehicle Detection ◽  
Obstacle Detection ◽  
Experimental Results ◽  
Geometrical Features ◽  
Traffic Environment ◽  
Novel Method ◽  
Shadow Cast

A novel method to detect vehicles is presented in the paper. Assumption of the vehicle is made using the geometrical features of the vehicle rear by the statistical histogram. Then hypothesis is verified using the property of the shadow cast by the car according to a prior acknowledgement of traffic scene. Finally, the vehicle detection is realized by hypothesis and verification of objects. The experimental results show the efficiency and feasibility of the method.

Novel Algorithmic Approach to Deciphering Rovash Inscriptions

2015 ◽  
pp. 7222-7233 ◽  
Author(s):  
Loránd Lehel Tóth ◽  
Raymond Pardede ◽  
Gábor Hosszú
Keyword(s):  
Experimental Results ◽  
The Novel ◽  
Statistical Probability ◽  
Algorithmic Approach ◽  
Topological Parameters ◽  
Novel Method ◽  
Novel Algorithm

The article presents a method to decipher Rovash inscriptions made by the Szekelys in the 15th-18th centuries. The difficulty of the deciphering work is that a large portion of the Rovash inscriptions contains incomplete words, calligraphic glyphs or grapheme errors. Based on the topological parameters of the undeciphered symbols registered in the database, the presented novel algorithm estimates the meaning of the inscriptions by the matching accuracies of the recognized graphemes and gives a statistical probability for deciphering. The developed algorithm was implemented in software, which also contains a built-in dictionary. Based on the dictionary, the novel method takes into account the context in identifying the meaning of the inscription. The proposed algorithm offers one or more words in a different random values as a result, from which users can select the relevant one. The article also presents experimental results, which demonstrate the efficiency of method.

Automated Ranking of Relaxing Query Results Based on XML Structure and Content Preferences

2013 ◽  
pp. 44-62
Author(s):  
Wei Yan ◽  
Li Yan ◽  
Z. M. Ma
Keyword(s):  
Structural Relaxation ◽  
User Studies ◽  
Experimental Results ◽  
Ranking Method ◽  
Ranking Algorithm ◽  
Efficiency And Effectiveness ◽  
Preference Query ◽  
The Many

This paper proposes a contextual preference query method of XML structural relaxation and content scoring to resolve the problem of empty or too many answers returned by XML. This paper proposes a XML contextual preference (XCP) model, where all the possible relaxing queries are determined by the users’ preferences. The XCP model allows users to express their interests on XML tree nodes, and then users assign interest scores to their interesting nodes for providing the best answers. A preference query results ranking method is proposed based on the XCP model, which includes: a Clusters_Merging algorithm to merge clusters based on the similarity of the context states, a Finding_Orders algorithm to find representative orders of the clusters, and a Top-k ranking algorithm to deal with the many answers problem. Results of preliminary user studies demonstrate that the method can provide users with most relevant and ranked query results. The efficiency and effectiveness of the approach are also demonstrated by experimental results.

scholarly journals Hierarchical Classification Based on Label Distribution Learning

2019 ◽  
Vol 33 ◽  
pp. 5533-5540 ◽  
Author(s):  
Changdong Xu ◽  
Xin Geng
Keyword(s):  
Hierarchical Classification ◽  
Experimental Results ◽  
Challenging Problem ◽  
Training Set ◽  
True Label ◽  
Major Bottleneck ◽  
Novel Method ◽  
Class Labels ◽  
Label Distribution ◽  
The Given

Hierarchical classification is a challenging problem where the class labels are organized in a predefined hierarchy. One primary challenge in hierarchical classification is the small training set issue of the local module. The local classifiers in the previous hierarchical classification approaches are prone to over-fitting, which becomes a major bottleneck of hierarchical classification. Fortunately, the labels in the local module are correlated, and the siblings of the true label can provide additional supervision information for the instance. This paper proposes a novel method to deal with the small training set issue. The key idea of the method is to represent the correlation among the labels by the label distribution. It generates a label distribution that contains the supervision information of each label for the given instance, and then learns a mapping from the instance to the label distribution. Experimental results on several hierarchical classification datasets show that our method significantly outperforms other state-of-theart hierarchical classification approaches.

scholarly journals Personalized Clothing Recommendation Based on User Emotional Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Xueping Su ◽  
Meng Gao ◽  
Jie Ren ◽  
Yunhong Li ◽  
Matthias Rätsch
Keyword(s):  
Facial Expression ◽  
Recommendation System ◽  
Experimental Results ◽  
Personalized Recommendation ◽  
Continuous Development ◽  
Expression Intensity ◽  
Novel Method ◽  
Multiclass Svm

With the continuous development of economy, consumers pay more attention to the demand for personalization clothing. However, the recommendation quality of the existing clothing recommendation system is not enough to meet the user’s needs. When browsing online clothing, facial expression is the salient information to understand the user’s preference. In this paper, we propose a novel method to automatically personalize clothing recommendation based on user emotional analysis. Firstly, the facial expression is classified by multiclass SVM. Next, the user’s multi-interest value is calculated using expression intensity that is obtained by hybrid RCNN. Finally, the multi-interest value is fused to carry out personalized recommendation. The experimental results show that the proposed method achieves a significant improvement over other algorithms.

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