·       ISI Web of Science citations: … (h-index: 24)

(As of December 2024)

LIST OF CITATIONS (December 2024)

Özgür Ulusoy

Abbreviations used for the type of citation:
ISI (ISI Web of Science)
ELWR (elsewhere)
*ISI and *ELWR denote self-citations

 

169.   Jizhe Xia, Optimizing an Index with Spatiotemporal Patterns to Support GEOSS Clearinghouse, M.S. Thesis, Department of Geography and Geoinformation Science, George Mason University, 2012. [ELWR]

 

 

 

1.     Li, ZY and Shao, XH. Future locations prediction with multi-graph attention networks based on spatial-temporal LSTM framework, Journal of Supercomputing, Early Access, 2024. [ISI]

2.     Yao, D; Guo, FD; (...); Bi, JPP. Trajectory Completion via Context-Guided Neural Filtering and Encoding, International Conference on Database Systems for Advanced Applications, pp.3-19, 2024. [ISI]

3.     Asri, H and Jarir, Z. Toward a smart health: big data analytics and IoT for real-time miscarriage prediction, Journal of Big Data, vol.10, no.1, 2023. [ISI]

4.     Xu, CY; Li, F and Xia, JZ. Fusing high-resolution multispectral image with trajectory for user next travel location prediction, International Journal of Applied Earth Observation and Geoinformation, vol.116, 2023. [ISI]

5.     Molina, E; Fiacchini, M; (...); Robu, B. Optimal privacy protection of mobility data: a predictive approach, IFAC PAPERSONLINE, vol.56, no.2, pp.11015-11020, 2023. [ISI]

6.     Su, J and Li, J. Recommendations for Crowdsourcing Services Based on Mobile Scenarios and User Trajectory Awareness, International Journal of Web Services Research, vol.19, no.1, pp.1-18, 2022. [ISI]

7.     Lv, MQ; Zeng, DJ; Ji, SL. Private Cell-ID Trajectory Prediction Using Multi-Graph Embedding and Encoder-Decoder Network, IEEE TRANSACTIONS ON MOBILE COMPUTING, vol.21, no.8, pp.2967-2977, 2022. [ISI]

8.     Masih, N and Ahuja, S, Application of data mining techniques for early detection of heart diseases using Framingham heart study dataset, International Journal of Biomedical Engineering and Technology, vol.38, no.4, pp.334-344, 2022. [ISI]

9.     Chekol, AG and Fufa, MS. A survey on next location prediction techniques, applications, and challenges, EURASIP Journal on Wireless Communications and Networking, 2022. [ISI]

10.  Sun, HL; Guo, XL; He, L, Predicting Future Locations with Semantic Trajectories, ACM Transactions on Intelligent Systems and Technology, vol.13, no.1, 2022. [ISI]

11.  Oueslati, W; Tahri, S; Akaichi, J. A New Approach for Predicting the Future Position of a Moving Object: Hurricanes' Case Study, Applied Artificial Intelligence, Early Access, 2022. [ISI]

12.  Xie, RB; Liu, JX; Xiang, JY, A Hybrid TLBO-TS Algorithm Based Mobile Service Selection for Composite Services, International Conference on Algorithms and Architectures for Parallel Processing, pp. 237-256, 2022. [ISI]

13.  Li, ZY; Ouyang, SR; Chen, GH, Two-Hop Relay Deployment Based on User Trajectory in Wireless Networks, Computer Journal, (Early Access), 2021. [ISI]

14.  Shrivastava, A; Verma, JPV; Garg, S, A deep learning based approach for trajectory estimation using geographically clustered data, Applied Sciences, vol.3, no.6, 2021. [ISI]

15.  Sun, J and Kim, J `Joint prediction of next location and travel time from urban vehicle trajectories using long short-term memory neural networks’, Transportation Research Part C – Emerging Technologies, vol.128, 2021. [ISI]

16.  Wang, WF; Zhu, KM; Song, XF, `Traffic speed mapping with cellular network signaling data by FOSS4G’, Spatial Information Research, Early Access, 2021. [ISI]

17.  Hosseinpoor Milaghardan, Amin; Ali Abbaspour, Rahim; Claramunt, Christophe; et al. An activity-based framework for detecting human movement patterns in an urban environment, Transactions in GIS, Early Access, 2021. [ISI]

18.  Wu, Sai; Pang, Zhifei; Chen, Gang; et al., NEIST: A Neural-Enhanced Index for Spatio-Temporal Queries, IEEE Transactions on Knowledge and Data Engineering, vol.33, no.4, pp.1659-1673, 2021. [ISI]

19.  Zhu, Kemin; Liu, Junli; Song, Xianfeng; et al. Refining Sparse Cell-ID Trajectory of Public Service Vehicles by Spatiotemporal Modelling, Journal of Advanced Transportation, vol.2021, Article Number: 1586010, 2021. [ISI]

20.  Cerf, Sophie; Bouchenak, Sara; Robu, Bogdan; et al. `Automatic Privacy and Utility Preservation for Mobility Data: A Nonlinear Model-Based Approach’, IEEE Transactions on Dependable and Secure Computing, vol.18, no.1, pp.269-282, 2021. [ISI]

21.  Kamal, Muhammad Daud; Tahir, Ali; Kamal, Muhammad Babar; et al. `A Survey for the Ranking of Trajectory Prediction Algorithms on Ubiquitous Wireless Sensors’, Sensors, vol.20, no.22, Article Number: 6495, 2020. [ISI]

22.  Yu, Bin; Cai, Mingjie; Dai, Jianhua; et al. `A novel approach to predictive analysis using attribute-oriented rough fuzzy sets’, Expert Systems with Applications, vol.161, Article Number: 113644, 2020. [ISI]

23.  Comito, Carmela `NexT: A framework for next-place prediction on location based social networks’, Knowledege Based Systems, vol.204, Article Number: 106205, 2020. [ISI]

24.  Verma, Jai Prakash V.; Mankad, Sapan H.; Garg, Sanjay `GeoHash tag based mobility detection and prediction for traffic management’, SN Applied Scienc‏es, vol.2, no.8, Article Number: 1385, 2020. [ISI]

25.  Chen, Jianwei; Li, Jianbo; Ahmed, Manzoor; et al. `Next Location Prediction with a Graph Convolutional Network Based on a Seq2seq Framework’, KSII Transactions on Internet and Information Systems, vol.14, no.5, pp.1909-1928, 2020. [ISI]

26.  Crivellari, Alessandro; Beinat, Euro `LSTM-Based Deep Learning Model for Predicting Individual Mobility Traces of Short-Term Foreign Tourists, Sustainability, vol.12, no.1, Article Number: 349, 2020. [ISI]

27.  Xiao, Yuelei; Nian, Qing `Vehicle Location Prediction Based on Spatiotemporal Feature Transformation and Hybrid LSTM Neural Network’, Information, vol.11, no.2, Article Number: 84, 2020. [ISI]

28.  Jiang, Yun; He, Wei; Cui, Lizhen; et al. `Spatial Task Allocation Based on User Trajectory Prediction’, Computer Supported Cooperative Work and Social Computing, Book Series: ‏ Communications in Computer and Information Science, vol.‏917, pp.386-397, 2019. [ISI]

29.  Gupta, Ajay K.; Shanker, Udai `SPMC-PRRP: A Predicted Region Based Cache Replacement Policy', International Conference on Data and Information Sciences (ICDIS), Lecture Notes in Networks and Systems, vol.39, pp.313-326, 2019. [ISI]

30.  Wu, Hongyue; Deng, Shuiguang; Li, Wei; et al. `Mobility-Aware Service Selection in Mobile Edge Computing Systems’, IEEE International Conference on Web Services, pp. 201-208, 2019. [ISI]

31.  Comito, Carmela, Mining Human Mobility from Social Media to support Urban Computing Applications, Annual International Conference on Distributed Computing in Sensor Systems, pp. 514-521, 2019. [ISI]

32.  Rathore, Punit; Kumar, Dheeraj; Rajasegarar, Sutharshan; et al. `A Scalable Framework for Trajectory Prediction’, IEEE Transactions on Intelligent Transportation Systems, vol.20, no.10, pp.3860-3874, 2019. [ISI]

33.  Dong, Yanjie; Polak, John; Sivakumar, Aruna; et al. `Disaggregate Short-Term Location Prediction Based on Recurrent Neural Network and an Agent-Based Platform’, Transportation Research Record, vol.2673, no.8, pp.657-668, 2019. [ISI]

34.  Lv, Mingqi; Chen, Ling; Chen, Tieming; et al. `Discovering individual movement patterns from cell-id trajectory data by exploiting handoff features’, Information Sciences, vol.474, pp. 18-32, 2019. [ISI]

35.  Lv, Mingqi; Zeng, Dajian; Chen, Tieming; et al. `A Sequence-to-Sequence Model for Cell-ID Trajectory Prediction’, ACM International Joint Conference on Pervasive and Ubiquitous Computing / ACM International Symposium on Wearable Computers, pp.137-140, 2019. [ISI]

36.  Yi, Feng; Feng, Guan; Wang, Hongtao; et al. `MIAC: A mobility intention auto-completion model for location prediction’, Intelligent Systems in Accounting Finance & Management, vol.25, no.4, pp.161-173, 2018. [ISI]

37.  Aghdam, Arash Hazeghi; Alesheikh, Ali Asghar `Predicting the future location of cars on urban street network by chaining spatial web services', IET Intelligent Transport Systems, vol.12, no.8, pp.793-800, 2018. [ISI]

38.  Qi, Weijing; Song, Qingyang; Wang, Xiaojie; et al. `SDN-Enabled Social-Aware Clustering in 5G-VANET Systems’, IEEE Access, vol.6, pp. 28213-28224, 2018. [ISI]

39.  Hashim, Emmy N.; Nohuddin, Puteri N. E. `Data Mining Techniques for Recidivism Prediction: A Survey Paper’, Advanced Science Letters, vol.24, no.3, pp.1616-1618, 2018. [ISI]

40.  Basiri, Anahid; Amirian, Pouria; Winstanley, Adam; et al. `Making tourist guidance systems more intelligent, adaptive and personalised using crowd sourced movement data’, Journal of Ambient Intelligence and Humanized Computing, vol.9, no.2, pp.413-427, 2018. [ISI]

41.  Naserian, Elahe; Wang, Xinheng; Dahal, Keshav; et al. `Personalized location prediction for group travellers from spatial-temporal trajectories’, Future Generation Computer Systems – The International Journal of Escience, vol.83, pp.278-292, 2018. [ISI]

42.  Wu, Ruizhi; Luo, Guangchun; Yang, Qinli; et al. `Learning Individual Moving Preference and Social Interaction for Location Prediction’, IEEE Access, vol.6, pp. 10675-10687, 2018. [ISI]

43.  Comito, Carmela `Mining Pattern Similarity for Mobility Prediction in Location-based Social Networks’, International Conference on Mobile and Ubiquitous Systems - Computing, Networking and Services, pp.284-291, 2018. [ISI]

44.  Yang, Qian; Cui, Lizhen; Zheng, Miao; et al. `LBTask: A Benchmark for Spatial Crowdsourcing Platforms’, International Conference on Crowd Science and Engineering, 2018. [ISI]

45.  Gupta, Ajay K.; Shanker, Udai `SPMC-CRP:A Cache Replacement Policy for Location Dependent Data in Mobile’, International Conference on Smart Computing and Communications, Procedia Computer Science, vol.125, pp.632-639, 2018. [ISI]

46.  Chawuthai, Rathachai; Chankaew, Nattaphon; Threepak, Thanunchai `A Hybrid Method for Predicting a Potential Next Rest Stop of Commercial Vehicles’, International Workshop on Traffic Data Collection and its Standardization, 2018. [ISI]

47.  Wu, Hongyue; Deng, Shuiguang; Li, Wei; et al. `Service Selection for Composition in Mobile Edge Computing Systems’, IEEE International Conference on Web Services, pp. 355-358, 2018. [ISI]

48.  Jitkajornwanich, Kulsawasd; Vateekul, Peerapon; Gupta, Upa; et al. `Ocean Surface Current Prediction Based on HF Radar Observations Using Trajectory-Oriented Association Rule Mining’, IEEE International Conference on Big Data, pp.4293-4300, 2017. [ISI]

49.  Comito, Carmela `Exploiting Twitter for Next-Place Prediction’, International Conference on Information Society (i-Society), pp.143-148, 2017. [ISI]

50.  Xiang, Shili; Li, Lu; Lo, Si Min; et al. `People-Centric Mobile Crowdsensing Platform for Urban Design’, Book Series: Lecture Notes in Artificial Intelligence,  vol.10604, pp.569-581, 2017. [ISI]

51.  Giang Minh Duc; Le Manh; Do Hong Tuan `A Method for Mobility Management in Cellular Networks Using Data Mining’, International Conference on Context-Aware Systems and Applications, Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering , vol.193, pp.193-204, 2017. [ISI]

52.  E. Cesario, C. Comito, D. Talia `An approach for the discovery and validation of urban mobility patterns’, Pervasive and Mobile Computing, vol.42, pp. 77-92, 2017. [ISI]

53.  F. Wu, K. Fu, Y. Wang, et al. `A Spatial-Temporal-Semantic Neural Network Algorithm for Location Prediction on Moving Objects’, Algorithms, vol.10, no.2, Article Number: 37, 2017. [ISI]

54.  M. J. Williams, R. M. Whitaker, M. Roger, S. M. Allen ` There and Back Again: Detecting Regularity in Human Encounter Communities’, IEEE Transactions on Mobile Computing, vol.16, no.5, pp. 1744-1757, 2017. [ISI]

55.  Y. Yan, Q. Pei, X. Wang, et al. `Probability-based prediction query algorithm’, Ad Hoc Networks, vol.60, pp.52-65, 2017. [ISI]

56.  C. Y. Tsai, M. H. Li, R. J. Kuo `A shopping behavior prediction system: considering moving patterns anti product characteristics’, Computers and Industrial Engineering, vol.106, pp.192-204, 2017. [ISI]

57.  A. Boukerche, A. Magnano, M. Aljeri `Mobile IP Handover for Vehicular Networks: Methods, Models, and Classifications’, ACM Computing Surveys, vol.49, no.4,  Article Number: 73, 2017. [ISI]

58.  Z. Yang, D. Lian, N. J.  Yuan, et al. ` Indigenization of urban mobility’, Physica A – Statistical Mechanics and Its Applications, vol.469, pp.232-243, 2017. [ISI]

59.  Q. Huang `Mining online footprints to predict user's next location’, International Journal of Geographical Information Science, vol.31, no.3, pp.523-541, 2017. [ISI]

60.  R. Trasarti, R. Guidotti, A. Monreale, et al. `MyWay: Location prediction via mobility profiling’, Information Systems, vol.64, pp. 350-367, 2017. [ISI]

  1. W. Zheng, X. Huang, Y. Li `Understanding the tourist mobility using GPS: Where is the next place?’, Tourism Management, vol.59, pp. 267-280, 2017. [ISI]
  2. L. D. M. Lam, A. Tang, J. Grundy `Predicting Indoor Spatial Movement Using Data Mining and Movement Patterns’, International Conference on Big Data and Smart Computing,   pp.223-230, 2017. [ISI]

63.  A. Basiri, M. Jackson, P. Amirian, et al. `Quality assessment of OpenStreetMap data using trajectory mining’, Geo-Spatial Information Science, vol.19, no.1, pp.56-68, 2016. [ISI]

  1. S. S. Vaithiya ` Resource availability prediction using semi-Markov model in mobile grid environment’, International Journal of Grid and Utility Computing, vol.7, no.4, pp.285-293, 2016. [ISI]
  2. L. D. M. Lam, A. Tang, J. Grundy `Heuristics-based indoor positioning systems: a systematic literature review’, Journal of Location Based Services, vol.10, no.3, pp. 178-211, 2016. [ISI]
  3. N. Zhang, H. Chen, X. Chen, et al. ` Forecasting Public Transit Use by Crowdsensing and Semantic Trajectory Mining: Case Studies’, ISPRS International Journal of Geo-Information, vol.5, no.10, Article Number: 180, 2016. [ISI]
  4. D. Guessoum, M. Miraoui, C. Tadj `Contextual location prediction using spatio-temporal clustering’, International Journal of Pervasive Computing and Communications, vol.12, no.3, pp. 290-309, 2016. [ISI]
  5. C. Colot, I. Linden, P. Baecke `A Survey on Mobile Data Uses’, International Journal of Decision Support System Technology, vol.8, no.2, pp.29-49, 2016. [ISI]
  6. M. Ficco, R. Pietrantuono, S. Russo ` Using multi-objective metaheuristics for the optimal selection of positioning systems’, Soft Computing, vol.20, no.7, pp.2641-2664, 2016. [ISI]
  7. M. Ozer, I. Keles, H. Toroslu, et al. `Predicting the Location and Time of Mobile Phone Users by Using Sequential Pattern Mining Techniques’, Computer Journal, vol.59, no.6, pp. 908-922, 2016. [ISI]
  8. R. Wang, C. Y. Chow, Y. Lyu, et al. `Exploring cell tower data dumps for supervised learning-based point-of-interest prediction', Geoinformatica, vol.20, no.2, pp.327-349, 2016. [ISI]
  9. K. Poularakis, L. Tassiulas `Cooperation and information replication in wireless networks’, Philosophical Transactions of the Royal Society A – Mathematical, Physical and Engineering Sciences, vol.374, issue.2062, Article Number: 20150123, 2016. [ISI]
  10. S. B. Cho `Exploiting machine learning techniques for location recognition and prediction with smartphone logs’, Neurocomputing, vol.176, pp. 98-106, 2016. [ISI]
  11. A. Pyrgelis, E. De Cristofaro, G. J.  Ross `Privacy-Friendly Mobility Analytics using Aggregate Location Data’, ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2016. [ISI]
  12. X. Xu, L. Xiong, V. Sunderam, et al. `A Markov Chain Based Pruning Method for Predictive Range Queries’,  ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2016. [ISI]
  1. X. Chen, D. Shi, B. Zhao, F. Liu `Periodic Pattern Mining Based on GPS Trajectories', International Symposium on Advances in Electrical, Electronics and Computer Engineering, pp.181-187, 2016. [ISI]
  1. E Cesario, C Comito, D Talia `A Comprehensive Validation Methodology for Trajectory Pattern Mining of GPS Data’, IEEE Intl Conf on Dependable, Autonomic and Secure Computing, pp. 819-826, 2016. [ISI]
  2. T. V. T. Duong, D. Q. Tran `A Fusion of Data Mining Techniques for Predicting Movement of Mobile Users’, Journal of Communications and Networks, vol.17, no.6, pp. 568-581, 2015. [ISI]
  1. Z. Yu, H. Wang, B. Guo, et al. `Supporting Serendipitous Social Interaction Using Human Mobility Prediction’, IEEE Transactions on Human-Machine Systems, vol.45, no.6, pp. 811-818, 2015. [ISI]
  2. M. Q. Lv, L. Chen, Y. B. Shen, G. C. Chen `Measuring cell-id trajectory similarity for mobile phone route classification’, Knowledge-Based Systems, vol.89, pp. 181-191, 2015. [ISI]
  3. M. Dash, G. G. Chua, N. Hai-Long, et al. `An Interactive Analytics Tool for Understanding Location Semantics and Mobility of Users Using Mobile Network Data’, IEEE International Conference on Mobile Data Management, pp.345-348, 2015. [ISI]
  4. B. A. Sabarish, R. Karthi, T. Gireeshkumar `A Survey of Location Prediction Using Trajectory Mining’, Artificial Intelligence and Evolutionary Algorithms in Engineering Systems, Book Series: Advances in Intelligent Systems and Computing   vol.324, pp.119-127, 2015. [ISI]
  5. C. C. Lee, J. W. Yoon `A Novel Statistical Approach to Detect Card Frauds Using Transaction Patterns’, IEICE Transactions on Information and Systems, vol. E98D, no.3, pp.649-660, 2015. [ISI]
  6. J. Alvarez-Lozano, J. A. Garcia-Macias, E.  Chavez `Crowd location forecasting at points of interest’, International Journal of Ad Hoc and Ubiquitous Computing, vol.18, no.4, pp.191-204, 2015. [ISI]
  7. C. Y. Tsai, B. H. Lai `A Location-Item-Time sequential pattern mining algorithm for route recommendation’, Knowledge-Based Systems, vol.73, pp. 97-110, 2015. [ISI]
  1. M. Vukovic, D. Jevtic `Agent-based Movement Analysis and Location Prediction in Cellular Networks’, International Conference on Knowledge Based and Intelligent Information and Engineering Systems, Procedia Computer Science, vol.60, pp.517-526, 2015. [ISI]
  2. A. Thomason, M. Leeke, N. Griffiths `Understanding the Impact of Data Sparsity and Duration for Location Prediction Applications’, International Summit on Internet of Things (IoT), Book Series: Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering, vol.151, pp.192-197, 2015. [ISI]
  3. H. Cui, X. Yin `Mining Users' Mobility Patterns Based On Apriori’, International Conference on Mechatronics, Materials, Chemistry and Computer Engineering, Book Series: ACSR-Advances in Comptuer Science Research, vol.39, pp.1176-1181, 2015. [ISI]
  4. W. Hou, B. Xian, L. Guo, W. Qi, H. Zhang `Novel routing algorithms in space information networks based on timeliness-aware data mining and time-space graph’, International Conference on Wireless Communications & Signal Processing, pg.1-5, 2015. [ISI]
  5. Thuy-Van T. Duong, Dinh Que Tran `Mobility prediction based on collective movement behaviors in public WLANs’, Science and Information Conference, pp. 1003–1010, 2015. [ISI]
  6. C. Ma, Y. Wang, H. Liu, H. Gui, W. Zhu, X. Shi, X. Li `An Approach to Social Relationship Ranking on Internet-Based Social Platforms by Tempo-spatial Data Mining Using Location Prediction Technique’, IEEE International Congress on Big Data (BigData Congress), pp.327-334, 2015. [ISI]
  7. Alexander Magnano, Xin Fei, Azzedine Boukerche `Predictive Mobile IP Handover for Vehicular Networks’, IEEE Conference on Local Computer Networks, pp.338-346, 2015. [ISI]
  8. A. Magnano, X. Fei, A. Boukerche `Movement Prediction in Vehicular Networks’, IEEE Global Communications Conference, 2015. [ELWR]
  1. M. Papandrea, S. Giordano `Location prediction and mobility modelling for enhanced localization solution’, Journal of Ambient Intelligence and Humanized Computing, vol.5, no.3, pp. 279-295, 2014. [ISI]
  2. X. Lu, Z. Qu, P. Lio, et al. `Directional communication with movement prediction in mobile wireless’, Personal and Ubiquitous Computing, vol.18, no.8, pp. 1941-1953, 2014. [ISI]
  3. J. Hao, G. Wang, B. Seo, et al. `Point of Interest Detection and Visual Distance Estimation for Sensor-Rich Video’, IEEE Transactions on Multimedia, vol.16, no.7, pp. 1929-1941, 2014. [ISI]
  4. J. C. Ying, H. S. Chen, K. W. Lin, et al. `Semantic trajectory-based high utility item recommendation system’, Expert Systems with Applications, vol.41, no.10, pp. 4762-4776, 2014. [ISI]
  5. Thi Hong Nhan Vu, Yang Koo Lee, The Duy Bui `A technique for extracting behavioral sequence patterns from GPS recorded data’, Computing, vol.96, no.3, pp. 163-188, 2014. [ISI]
  6. K. Farrahi, D. Gatica-Perez ` A probabilistic approach to mining mobile phone data sequences’, Personal and Ubiquitous Computing, vol.18, no.1, pp. 223-238, 2014. [ISI]
  7. M. Zignani, M. Papandrea, S. Gaito, et al. `On the key features in human mobility: relevance, time and distance’, IEEE International Conference on Pervasive Computing and Communication, pp. 260-265, 2014. [ISI]
  8. S. Naimi, A. Busson, V. Veque, et al. `Anticipation of ETX Metric to Manage Mobility in Ad Hoc Wireless Networks’, International Conference on Ad-Hoc Networks and Wireless, Lecture Notes in Computer Science, vol.8487, pp.29-42, 2014. [ISI]
  9. A. Basiri, P. Amirian `Automatic Point of Interests Detection Using Spatio-Temporal Data Mining Techniques over Anonymous Trajectories’, International Conference on Computational Science and Its Applications, Lecture Notes in Computer Science, vol.8582, pp.185-198, 2014. [ISI]
  10. Josh Jia-Ching Ying, Wang-Chien Lee, Vincent S. Tseng `Mining Geographic-Temporal-Semantic Patterns in Trajectories for Location Prediction’, ACM Transactions on Intelligent Systems and Technology, vol.5, no.1, Article Number: 2, 2013. [ISI]
  11. W. Wanalertlak, B. Lee, C. Yu, et al. `Scanless fast handoff technique based on global Path-Cache for WLANs', Journal of Supercomputing, vol.66, no.3, pp.1320-1349, 2013. [ISI]
  12. X. F. Lu, P. Lio, P. Hui, et al. `A Location Prediction Algorithm for Mobile Communications Using Directional Antennas', International Journal of Distributed Sensor Networks, Article no.418606, 2013. [ISI]
  13. C. Wang, D. De, W. Z. Song `Trajectory mining from anonymous binary motion sensors in Smart Environment', Knowledge-Based Systems, vol.37, pp.346-356, 2013. [ISI]
  14. Y. H. Kim, Y. Yoon `Context Prediction of Mobile Users Based on Time-Inferred Pattern Networks: A Probabilistic Approach', Mathematical Problems in Engineering, Article Number: 106139, 2013. [ISI]
  15. Jaek Wang Kim, Seung Hoon Lee, Hye Wuk Jung, Jee Hyong Lee `A Path Summarization and Prediction Method Based on Meaningful Locations', Applied Mechanics and Materials, vol.321-324, pp.2047-2055, 2013. [ISI]
  16. Y. J. Kim, S. B. Cho `A HMM-Based Location Prediction Framework with Location Recognizer Combining k-Nearest Neighbor and Multiple Decision Trees’, International Conference on Hybrid Artificial Intelligent Systems, Lecture Notes in Computer Science, vol. 8073, pp.618-628, 2013. [ISI]
  17. Chieh-Yuan Tsai, Bo-Han Lai `Customized Visiting Route Service under RFID Environment’, IEEE Annual Computer Software and Applications Conference Workshops, pp.397-402, 2013. [ISI]
  18. M. Abo-Zahhad, S. M. Ahmed, M. Mourad `Future Location Prediction of Mobile Subscriber over Mobile Network Using Intra Cell Movement Pattern Algorithm', International Conference on Communications, Signal Processing, and their Applications, 2013. [ISI]
  1. Jae Sung Lee, Eun Sung Lee `Exploring the Usefulness of a Decision Tree in Predicting People's Locations’, Procedia - Social and Behavioral Sciences, vol.140, pp. 447–451, 2013. [ISI]
  2. R. Assam, T. Seidl `BodyGuards: A Clairvoyant Location Predictor Using Frequent Neighbors and Markov Model’, IEEE International Conference on Ubiquitous Intelligence and Computing, 2013. [ISI]
  1. L. C. Ying, C. Y. Chin, V. S. Tseng `Mining Web Navigation Patterns with Dynamic Thresholds for Navigation Prediction’, IEEE International Conference on Granular Computing, pp. 614-619, 2012. [ISI]
  2. R. Matos, S. Sargento, K. A. Hummel, et al. `Context-based wireless mesh networks: a case for network virtualization', Telecommunication Systems, vol.51, no.4, pp.259-272, 2012. [ISI]
  3. D. Riboni, C. Bettini `Context provenance to enhance the dependability of ambient intelligence systems', Personal and Ubiquitous Computing, vol.16, no.7, pp.799-818, 2012. [ISI]
  4. T. S. Chen, Y. S. Chou, T. C. Chen `Mining User Movement Behavior Patterns in a Mobile Service Environment', IEEE Transactions on Systems, Man and Cybernetics, Part-A Systems and Humans, vol.42, no.1, pp.87-101, 2012. [ISI]
  5. C. S. Lee, Y. K. Lee, S. G. Kang, et al. `Classifications and Research Trends of Data Analysis Techniques in Web and Mobile Environment', Information - An International Interdisciplinary Journal, vol.15, no.5, pp.2289-2298, 2012. [ISI]
  6. S. Boudko, W. Leister, S. Gjessing `Team Decision Approach for Decentralized Network Selection of Mobile Clients', Wireless and Mobile Networking Conference, Book Series: Joint IFIP Wireless and Mobile Networking Conference, pp. 88-94, 2012. [ISI]
  7. R. Li, J. Shen, J. Chen, et al. `A Vertical Handoff Decision Algorithm based on ARMA Prediction Model', International Conference on Machine Vision- Machine Vision, Image Processing and Pattern Analysis, Book Series: Proceedings of SPIE, vol.8349, Article Number: 83492J, 2012. [ISI]
  8. B. Deng, J. Ji `Study on prediction model of context-aware services technologies for internet of things’, International Conference on Communications and Information Processing, Book Series: Communications in Computer and Information Science, vol.288, pp.159-168, 2012. [ISI]
  9. H. J. Li, G. Ascheid `Mobility Prediction based on Graphical Model Learning', IEEE Vehicular Technology Conference, 2012. [ISI]
  10. O. Kwon, K. Y. Kim `A Context Prediction Methodology for Timely Service Invocation in Location-Based', Information - An International Interdisciplinary Journal, vol.14, no.9, pp.2947-2959, 2011. [ISI]
  11. W. Wanalertlak, B. Lee, C. Yu, et al. `Behavior-based mobility prediction for seamless handoffs in mobile wireless networks', Wireless Networks, vol.17, no.3, pp.645-658, 2011. [ISI]
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204.                  Svetlana Boudko, Wolfgang Leister, Stein Gjessing `Multicast Group Management for Users of Heterogeneous Wireless Networks’, CONTENT 2012 : The Fourth International Conference on Creative Content Technologies, 2012. [ELWR]

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·        H. Aksu, I. Korpeoglu, Ö. Ulusoy `An Analysis of Social Networks Based on Tera-Scale Telecommunication Datasets’, IEEE Transactions on Emerging Topics in Computing, vol.7, no.2, pp. 349-360, 2019.

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·       T. Yilmaz, Ö. Ulusoy `Misinformation Propagation in Online Social Networks: Game Theoretic and Reinforcement Learning Approaches, IEEE Transactions on Computational Social Systems, vol.10, no.6, 2023.

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·       T. Yilmaz, Ö. Ulusoy `Modeling and Mitigating Online Misinformation: a Suggested Blockchain Approach’, arXiv preprint arXiv:2303.10765, 2024.

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·       T. Yilmaz, Ö. Ulusoy, `Understanding security vulnerabilities in student code: A case study in a non-security courseJournal of Systems and Software, vol.185, 2022.

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·       H. A. Caferoğlu, Ö. Ulusoy `E-SQL: Direct Schema Linking via Question Enrichment in Text-to-SQL’, arXiv preprint arXiv:2409.16751, 2024.

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4.     Vanderschantz, N and Hinze, A. Children's query formulation and search result exploration, International Journal on Digital Libraries, vol.22, no.4, pp.385-410, 2021. [ISI]

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1.     Alani, AA and Al-Azzawi, A. Optimizing web page retrieval performance with advanced query expansion: leveraging ChatGPT and metadata-driven analysis, JOURNAL OF SUPERCOMPUTING, vol.81, no.4, 2025. [ISI]

2.     Leung, J. Improving Educators' Search Engine Experience: A Quantitative Analysis of Search Terms, IEEE Access, vol.12, pp.69076-69086, 2024. [ISI]

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4.     Dong, S; Tao, XY; (...); Sun, JW. Advanced Mathematics Exercise Recommendation Based on Automatic Knowledge Extraction and Multilayer Knowledge Graph, IEEE Transactions on Learning Technologies vol.17, pp.776-793, 2024. [ISI]

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6.     Sebastian, R. Adaptive Search Support for Teachers in Lesson Planning, ACM Conference on User Modeling, Adaptation and Personalization, pp.20-24, 2024. [ISI]

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8.     Kataria, A; Venkateshprasanna, HM and Kummetha, AKR. Learning to Rank for Search Results Re-ranking in Learning Experience Platforms, Annual ACM India Compute Conference, pp.25-30, 2023. [ISI]

9.     Kataria, A; Venkateshprasanna, HM and Kummetha, AKR. Learning to Rank for Search Results Re-ranking in Learning Experience Platforms, Annual ACM India Compute Conference, pp.25-30, 2023. [ISI]

10.  Allen, G; Wright, KL; (...); Pera, MS. Multi-Perspective Learning to Rank to Support Children's Information Seeking in the Classroom, IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology, pp.311-317, 2023. [ISI]

11.  Chen, Y; Sun, XR; (...); Liang, CJ. A Prediction and Visual Analysis Method for Graduation Destination of Undergraduates Based on LambdaMART Model, International Journal of Information and Communication Technology Education, vol.18, no.2, 2022. [ISI]

12.  Yang, T; Luo, C; (...); Ai, QY. Can Clicks Be Both Labels and Features? Unbiased Behavior Feature Collection and Uncertainty-aware Learning to Rank, International ACM SIGIR Conference on Research and Development in Information Retrieval, pp.6-17, 2022. [ISI]

13.  Tao, D. Dynamic Web Page Graphic Design Method for Internet Big Data Information System, Mathematical Problems in Engineering, Article Number 6753671, 2022. [ISI]

14.  Sharma, PS; Yadav, D and Thakur, RN. Web Page Ranking Using Web Mining Techniques: A Comprehensive Survey, Mobile Information Systems, 2022. [ISI]

15.  Landoni, M; Aliannejadi, M; (...); Pera, MS, Have a Clue! The Effect of Visual Cues on Children's Search Behavior in the Classroom, ACM SIGIR Conference on Human Information Interaction and Retrieval, pp.310-314, 2022. [ISI]

16.  He, QH; Li, XJ and Sun, Y, Company Ranking Prediction Based on Network Big Data, Early Access, IETE Journal of Research, 2021. [ISI]

 

1.     Perezhohin, Y; Peres, F and Castelli, M. Combining computational linguistics with sentence embedding to create a zero-shot NLIDB, Array, vol.24, 2024. [ISI]

2.     Koutrika, G. Natural Language Data Interfaces: A Data Access Odyssey, International Conference on Database Theory, 2024. [ISI]

3.     Qiao, SJ; Liu, CX; (...); Yuan, G. GTR: An SQL Generator With Transition Representation in Cross-Domain Database Systems, IEEE Transactions on Neural Networks and Learning Systems, Early Access, 2023. [ISI]

4.     Katsogiannis-Meimarakis, G and Koutrika, G. A survey on deep learning approaches for text-to-SQL, VLDB Journal, Early Access, 2023. [ISI]

5.     A. Usta, A. Karakayalı, O. Ulusoy, xDBTagger: explainable natural language interface to databases using keyword mappings and schema graph, VLDB Journal, Early Access, 2023. [*ISI]