Matthias Renz - Academia.edu (original) (raw)

Papers by Matthias Renz

Results in control and optimization, Mar 1, 2023

During the last decade, a variety of social networks and applications has been developed, providi... more During the last decade, a variety of social networks and applications has been developed, providing to the users a set of potential functionalities. Thanks to these functionalities, they have become vital part of the daily life of many people. As a result, a great volume of data has been created. Due to the different nature of the functionalities, datasets of different nature and schema are created. This paper introduces GeoTe-Gra, a system that targets to reveal non-obvious knowledge by connecting datasets that derive from multiple heterogeneous sources. GeoTeGra is a scalable framework to compare different machine learning algorithms in terms of scalability and effectiveness, finding semantic similarities between entities. Our system is based on a distributed storage and parallel map-reduce manipulation for the fast retrieval of information from multi-class feature representations.

Lecture Notes in Computer Science, 2017

The increasing popularity of location-based applications creates new opportunities for users to t... more The increasing popularity of location-based applications creates new opportunities for users to travel together. In this paper, we study a novel spatio-social optimization problem, i.e., Optimal Group Route, for multi-user itinerary planning. With our problem formulation, users can individually specify sources and destinations, preferences on the Point-of-interest (POI) categories, as well as the distance constraints. The goal is to find a itinerary that can be traversed by all the users while maximizing the group’s preference of POI categories in the itinerary. Our work advances existing group trip planning studies by maximizing the group’s social experience. To this end, individual preferences of POI categories are aggregated by considering the agreement and disagreement among group members. Furthermore, planning a multi-user itinerary on large real-world networks is computationally challenging. We propose one approximate solution with bounded approximation ratio and one exact solution which computes the optimal itinerary by exploring a limited number of paths in the road network. In addition, an effective compression algorithm is developed to reduce the size of the network, providing a significant acceleration in our exact solution. We conduct extensive empirical evaluations on the road network and POI datasets of Los Angeles and our results confirm the effectiveness and efficiency of

SIGSPATIAL Special

The amount of publicly available geo-referenced data has seen a dramatic increase over the last y... more The amount of publicly available geo-referenced data has seen a dramatic increase over the last years. Many user activities generate data that are annotated with location and contextual information. It has also become easier to collect and combine rich and diverse location information. In the context of geoadvertising, the use of geosocial data for targeted marketing is receiving significant attention from a wide spectrum of companies and organizations. With the advent of smartphones and online social networks, a multi-billion dollar industry that utilizes geosocial data for advertising and marketing has emerged. Geotagged social-media posts, GPS traces, data from cellular antennas and WiFi access points are used widely to directly access people for advertising, recommendations, marketing, and group purchases. Exploiting this torrent of geo-referenced data provides a tremendous potential to materially improve existing recommendation services and offer novel ones, with numerous appli...

The amount of available geo-referenced data has seen a dra-matic explosion over the past few year... more The amount of available geo-referenced data has seen a dra-matic explosion over the past few years. Human activities now generate digital traces that are annotated with loca-tion data, enabling the collection of rich information about people’s interests and habits. This torrent of geo-referenced data provides a tremendous potential to augment recom-mender systems. The LocalRec’15 workshop brings together scholars from location-based services and recommender sys-tems, and seeks to set out new trends and research direc-tions.

SIGSPATIAL Special, 2017

This is the conference report on the 24 th ACM SIGSPATIAL International Conference on Advances in... more This is the conference report on the 24 th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2016), held in the San Francisco Bay Area, California, USA, October 31 through November 3, 2016. The conference started as a series of symposia and workshops back in 1993 with the aim of promoting interdisciplinary discussions among researchers, developers, users, and practitioners and fostering research in all aspects of geographic information systems, especially in relation to novel systems based on geospatial data and knowledge. It provides a forum for original research contributions covering all conceptual, design, and implementation aspects of geospatial data ranging from applications, user interfaces and visualization, to data storage, query processing, indexing and data mining. The conference is the premier annual event of the ACM Special Interest Group on Spatial Information (ACM SIGSPATIAL).

EPIC35th Data Science Symposium, Online/ Kiel, 2021-01-22-2021-01-22Kiel, GEOMAR, Jan 22, 2021

The following summary tries to capture a collection of state-of-the-art techniques and challenges... more The following summary tries to capture a collection of state-of-the-art techniques and challenges for future work on lineage management in uncertain and probabilistic databases that we discussed in our working group. It was one half of a larger committee that we had initially formed, which then got split into two groups---one focusing on lineage as a means of explanation of data, and one focusing more on lineage usage in probabilistic databases (see also the "Explanation" working group report for more details on the first subgroup).

SIGSPATIAL Special, 2016

This is the conference report of the 23 rd ACM SIGSPATIAL International Conference on Advances in... more This is the conference report of the 23 rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2015), held in Seattle, Washington, USA, November 3-6, 2015. This conference was the twenty-third edition in a series of symposia and workshops that began in 1993 with the aim of promoting interdisciplinary discussions among researchers, developers, users, and practitioners and fostering research in all aspects of geographic information systems, especially in relation to novel systems based on geospatial data and knowledge. The conference is the premier annual event of the ACM Special Interest Group on Spatial Information (ACM SIGSPATIAL) and provides a forum for original research contributions covering all conceptual, design, and implementation aspects of geospatial data ranging from applications, user interfaces, and visualization to data storage, query processing, indexing and data mining.

Encyclopedia of GIS, 2016

Das zahlreiche Fachrichtungen und Institutionen umfassende Netzwerk NFDI4Objects beschäftigt sich... more Das zahlreiche Fachrichtungen und Institutionen umfassende Netzwerk NFDI4Objects beschäftigt sich mit den materiellen Überresten der Menschheit aus einem Zeitraum von mehr als 2,6 Millionen Jahren. Aufbau und Ziele sowie die unterschiedlichen Task Areas werden im Folgenden vorgestellt. Dieser Artikel wurde zunächst analog im BLiCKpunkt Archäologie Heft 2/2021, Seite 150-164 veröffentlicht.

IEEE Transactions on Knowledge and Data Engineering, 2018

18th International Conference on Scientific and Statistical Database Management (SSDBM'06)

Lecture Notes in Computer Science, 2015

Proceedings of the 27th International Conference on Scientific and Statistical Database Management, 2015

Fuzzy object databases are becoming more and more important in the context of image analysis. Exa... more Fuzzy object databases are becoming more and more important in the context of image analysis. Examples include satellite images where blurred trees, houses or lakes can still be organized and searched in a meaningful manner and biomedical images which can be utilized to find similar disease patterns and monitor disease progress. One problem of the underlying data is that it contains blurred image content, i.e., fuzzy data. Therefore, an image-based similarity search, which can process huge amounts of fuzzy data in an efficient and effective way, is desirable. The aim of this work is to develop efficient and effective methods for similarity search in fuzzy object databases. First, a suitable similarity measure based on a shape similarity is proposed. Based on this, two novel k-nearest neighbor algorithms for efficient similarity search are presented. The first approach gains efficiency at the cost of incurring only approximate results, while the second approach uses a filter-refinement approach to prune computation. Our experimental evaluation shows the efficiency of the proposed algorithms.

The join query is a very important database primitive. It combines two datasets R and S (R = S in... more The join query is a very important database primitive. It combines two datasets R and S (R = S in case of a self-join) based on some query predicate into one set such that the new set contains pairs of objects of the two original sets. In various application areas, e.g. sensor databases, location-based services or face recognition systems, joins