Aarhus Universitets segl

Davide Mottin

Tenure Track Adjunkt

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Davide Mottin

Tenure Track Adjunkt

  • Institut for Datalogi
Postaddresse:
Åbogade 34
5335, 353
8200
Aarhus N
Danmark

E-mail: davide@cs.au.dk

Ansættelse

Tenure Track Adjunkt

Institut for Datalogi

Aarhus Universitet

Aarhus N, Danmark

1 okt. 2018 → nu

Publikationer

GRASP: Scalable Graph Alignment by Spectral Corresponding Functions

Hermanns, J., Skitsas, K., Tsitsulin, A., Munkhoeva, M., Kyster, A., Nielsen, S., Bronstein, A. M., Mottin, D. & Karras, P., maj 2023, I: ACM Transactions on Knowledge Discovery from Data. 17, 4, s. 1-26 50.

Comprehensive Evaluation of Algorithms for Unrestricted Graph Alignment

Skitsas, K., University, D. O. C. S., Hermanns, J., Mottin, D. & Karras, P., 2023, I: Advances in Database Technology - EDBT. s. 260-272 13 s.

GiDR-DUN; Gradient Dimensionality Reduction -- Differences and Unification

Draganov, A., Berry, T., Jørgensen, J. R., Nellemann, K. S., Assent, I. & Mottin, D., 20 jun. 2022.

Knowledge Graph Exploration Systems: are we lost?

Lissandrini, M., Mottin, D., Hose, K. & Pedersen, T. B., jan. 2022. 8 s.

UCoDe: Unified Community Detection with Graph Convolutional Networks

Moradan, A., Draganov, A., Mottin, D. & Assent, I., 29 dec. 2021.

Boosting Graph Alignment Algorithms

Kyster, A. F., Nielsen, S. D., Hermanns, J., Mottin, D. & Karras, P., okt. 2021, Proceedings of the 30th ACM International Conference on Information & Knowledge Management (CIKM '21). New York: Association for Computing Machinery, s. 3166-3170 5 s.

GRASP: Graph Alignment through Spectral Signatures

Hermanns, J., Tsitsulin, A., Munkhoeva, M., Bronstein, A., Mottin, D. & Karras, P., 10 jun. 2021, Web and Big Data. Hou U, L., Spaniol, M., Sakurai, Y. & Chen, J. (red.). Springer, s. 44-52 9 s. (Lecture Notes in Computer Science, Bind 12858).

SOFOS: Demonstrating the Challenges of Materialized View Selection on Knowledge Graph

Troullinou, G., Kondylakis, H., Lissandrini, M. & Mottin, D., jun. 2021, Proceedings of the 2021 International Conference on Management of Data (SIGMOD/PODS '21). New York: Association for Computing Machinery, s. 2789–2793 5 s.

Few-Shot Knowledge Validation using Rules

Loster, M., Mottin, D., Papotti, P., Ehmüller, J., Feldmann, B. & Naumann, F., 19 apr. 2021, The Web Conference 2021 - Proceedings of the World Wide Web Conference, WWW 2021. Leskovec, J., Grobelnik, M., Najork, M., Tang, J. & Zia, L. (red.). New York: Association for Computing Machinery, s. 3314-3324 11 s.

FREDE: Anytime Graph Embeddings

Tsitsulin, A., Munkhoeva, M., Mottin, D., Karras, P., Oseledets, I. & Mueller, E., feb. 2021, I: Proceedings of the VLDB Endowment. 14, 6, s. 1102-1110 9 s.

The Shape of Data: Intrinsic Distance for Data Distributions

Tsitsulin, A., Munkhoeva, M., Mottin, D., Karras, P., Bronstein, A., Oseledets, I. & Müller, E., 26 apr. 2020.

Graph-Query Suggestions for Knowledge Graph Exploration

Lissandrini, M., Mottin, D., Palpanas, T. & Velegrakis, Y., 2020, WWW '20: Proceedings of The Web Conference 2020. Huang, Y., King, I., Liu, T-Y. & van Steen, M. (red.). New York: Association for Computing Machinery, s. 2549-2555 7 s.

Knowledge Graph Exploration: Where Are We and Where Are We Going?

Lissandrini, M., Pedersen, T. B., Hose, K. & Mottin, D., 2020, I: S I G W E B Newsletter. Summer, 8 s., 4.

What if Neural Networks had SVDs?

Mathiasen, A., Hvilshøj, F., Jørgensen, J. R., Nasery, A. & Mottin, D., 2020, Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020). Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M. F. & Lin, H. (red.).

Figuring out the User in a Few Steps: Bayesian Multifidelity Active Search with Cokriging

Klyuchnikov, N., Mottin, D., Koutrika, G., Müller, E. & Karras, P., aug. 2019, KDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. Association for Computing Machinery, s. 686-695 10 s.

Spectral graph complexity

Tsitsulin, A., Mottin, D., Karras, P., Bronstein, A. & Müller, E., maj 2019, The Web Conference 2019 - Companion of the World Wide Web Conference, WWW 2019. Liu, L. & White, R. (red.). Association for Computing Machinery, s. 308-309 2 s.

Example-based Search: A new frontier for exploratory search

Lissandrini, M., Mottin, D., Palpanas, T. & Velegrakis, Y., 2019, SIGIR 2019 - Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, s. 1411-1412 2 s.

Exploring the Data Wilderness through Examples

Mottin, D., Lissandrini, M., Velegrakis, Y. & Palpanas, T., 2019, Proceedings of the 2019 International Conference on Management of Data. Association for Computing Machinery, s. 2031-2035 5 s.

Mining Patterns in Graphs with Multiple Weights

Preti, G., Lissandrini, M., Mottin, D. & Velegrakis, Y., 2019, I: Distributed and Parallel Databases. 39, 39 s.

Personalized Knowledge Graph Summarization: From the Cloud to Your Pocket

Safavi, T., Belth, C., Faber, L., Mottin, D., Müller, E. & Koutra, D., 2019. 10 s.

Data Exploration using Example-based Methods

Lissandrini, M., Mottin, D., Palpanas, T. & Velegrakis, Y., 1 dec. 2018, Morgan & Claypool Publishers. 164 s. (Synthesis Lectures on Data Management).

MetaExp: Interactive Explanation and Exploration of Large Knowledge Graphs

Behrens, F., Bischoff, S., Ladenburger, P., Rückin, J., Seidel, L., Stolp, F., Vaichenker, M., Ziegler, A., Mottin, D., Aghaei, F., Müller, E., Preusse, M., Müller, N. & Hunger, M., 23 apr. 2018, I: The Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018. s. 199-202 4 s.

Multi-Example Search in Rich Information Graphs

Lissandrini, M., Mottin, D., Velegrakis, Y. & Palpanas, T., 1 apr. 2018, 34rd IEEE International Conference on Data Engineering, ICDE 2018, Paris, France, April 16-19, 2018. 12 s.

Beyond Frequencies: Graph Pattern Mining in Multi-weighted Graphs.

Preti, G., Lissandrini, M., Mottin, D. & Velegrakis, Y., 1 mar. 2018, Proceedings of the 21st International Conference on Extending Database Technology (EDBT). openproceedings.org, s. 169-180 12 s. (Proceedings of the 21st International Conference on Extending Database Technology (EDBT),).

Notable Characteristics Search through Knowledge Graphs

Mottin, D., Grasnick, B., Kroschk, A., Siegler, P. & Mueller, E., 12 feb. 2018, Advances in Database Technology — EDBT 2018. openproceedings.org, Bind 2018. s. 429-432 4 s. (Proceedings of the 21st International Conference on Extending Database Technology (EDBT),).

X2Q: Your personal example-based graph explorer

Lissandrini, M., Mottin, D., Velegrakis, Y. & Palpanas, T., 1 jan. 2018, I: Proceedings of the VLDB Endowment. 11, 12, s. 2026-2029 4 s.

NetLSD: Hearing the Shape of a Graph

Tsitsulin, A., Mottin, D., Karras, P., Bronstein, A. & Müller, E., 2018, 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. Guo, Y. & Farooq, F. (red.). Association for Computing Machinery, s. 2347-2356 10 s.

VERSE: Versatile Graph Embeddings from Similarity Measures

Tsitsulin, A., Mottin, D., Karras, P. & Müller, E., 2018, Proceedings of the 2018 World Wide Web Conference: WWW '18. Champin, P-A., Gandon, F. & Médini, L. (red.). Association for Computing Machinery, s. 539-548 10 s.

New trends on exploratory methods for data analytics

Mottin, D., Lissandrini, M., Velegrakis, Y. & Palpanas, T., 1 aug. 2017, I: Proceedings of the VLDB Endowment. 10, 12, s. 1977-1980 4 s.

Graph exploration: From users to large graphs

Mottin, D. & Müller, E., 9 maj 2017, SIGMOD 2017 - Proceedings of the 2017 ACM International Conference on Management of Data. Association for Computing Machinery, Inc., Bind Part F127746. s. 1737-1740 4 s.

Exemplar queries: a new way of searching

Mottin, D., Lissandrini, M., Velegrakis, Y. & Palpanas, T., 1 dec. 2016, I: VLDB Journal. 25, 6, s. 741-765 25 s.

A holistic and principled approach for the empty-answer problem

Mottin, D., Marascu, A., Roy, S. B., Das, G., Palpanas, T. & Velegrakis, Y., 1 aug. 2016, I: VLDB Journal. 25, 4, s. 597-622 26 s.

Graph query reformulation with diversity

Mottin, D., Bonchi, F. & Gullo, F., 10 aug. 2015, KDD 2015 - Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, Inc., Bind 2015-August. s. 825-834 10 s.

Exemplar queries: Give me an example of what you need

Mottin, D., Lissandrini, M., Velegrakis, Y. & Palpanas, T., 1 jan. 2014, I: Proceedings of the VLDB Endowment. 7, 5, s. 365-376 12 s.

IQR: An interactive query relaxation system for the empty-answer problem

Mottin, D., Marascu, A., Roy, S. B., Das, G., Palpanas, T. & Velegrakis, Y., 1 jan. 2014, SIGMOD 2014 - Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data. Association for Computing Machinery, Inc., s. 1095-1098 4 s.

Searching with XQ: The Exemplar query search engine

Mottin, D., Lissandrini, M., Velegrakis, Y. & Palpanas, T., 1 jan. 2014, SIGMOD 2014 - Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data. Association for Computing Machinery, Inc., s. 901-904 4 s.

Unleashing the power of information graphs

Lissandrini, M., Mottin, D., Palpanas, T., Papadimitriou, D. & Velegrakis, Y., 1 jan. 2014, I: SIGMOD Record. 43, 4, s. 21-26 6 s.

A Probabilistic Optimization Framework for the Empty-Answer Problem

Mottin, D., Marascu, A., Basu Roy, S., Das, G., Palpanas, T. & Velegrakis, Y., 2013, I: PVLDB. 6, 14

Entity ranking using click-log information

Mottin, D., Palpanas, T. & Velegrakis, Y., 2013, I: Intelligent Data Analysis. 17, 5, s. 837-856 20 s.