Research profile

This page describe my research profile including research efforts that I have been part of and my current research activities.

Current Research Activites

I am currently leading a research initiative within data and information management in large scale environments. We are specifically interested in dealing with Big Data seen from both mathematical and statistical, and computational perspectives.

My current interests lie within web-based social media and finding . As part of this research effort my goal is to develop a computational framework dealing with the aspects of web mining towards providing good predictions in social media. Specifically, I will focus on the following research topics:

  • Extracting sentiment information from shared web sources to predict users' object preferences.

  • Developing efficient indexing techniques for high-performance information access.

  • Mining publicly shared resources to link and populate knowledge bases.

  • Retrieving entities towards effective cumulative citation recommendation.

Relevant papers so far

  1. M. Ruocco and H. Ramampiaro, (2015), "Geo-Temporal Distribution of Tag Terms for Event-Related Image Retrieval". In Information Processing & Management Journal (IPM), 51(1), pp. 92-110. Elsevier. ISSN: 0306-4573. Impact Factor: 1.069 (2013). (Published online Sept. 2014).

  2. H. T. Nguyen, M. Havig, H. Schistad, T. Almenningen, A. Kofod-Petersen, H. Langseth and H. Ramampiaro, (2014), "Learning to Rank for Personalized Fashion Recommender Systems via Implicit Feedback". 2nd International Conference on Mining Intelligence and Knowledge Exploration (MIKE 2014). Springer.

  3. Ruocco, M. and H. Ramampiaro, (2014), In Multimedia Tools and Applications Journal (MTAP), 70(1), pp. 55-88. Springer. ISSN: 1380-7501. Impact Factor: 1.058 (2013). (Published online May 2012).

  4. M. Ruocco and H. Ramampiaro, (2013), "Event-Related Image Retrieval: Exploring Geographical and Temporal Distribution of User Tags". In International Journal of Multimedia Information Retrieval (JMIR), 2(4), pp 273-288. Springer. ISSN: 2192-6611.

  5. K. Balog and H. Ramampiaro, (2013), "Cumulative Citation Recommendation: Classification vs. Ranking". In Proc. of the 36th ACM SIGIR Conference (SIGIR 2013). ACM Press.

  6. M. Ruocco and H. Ramampiaro, (2013), "Exploring Temporal Proximity and Spatial Distribution of Terms in Web-based Search of Event-Related Images". In Proc. of the 24th ACM Conference on Hypertext and Social Media (HT 2013). ACM Press.

  7. K. Balog, H. Ramampiaro, and K. Nørvåg., (2013), "KBAAA: A Web-based Toolkit for the Assessment and Analysis of Knowledge Base Acceleration Systems". In Proc. of Open research Areas in Information Retrieval Conference (OAIR 2013). ACM Press.
  8. K. Balog, H. Ramampiaro, N. Takhirov, and K. Nørvåg., (2013), "Multi-step Classification Approaches to Cumulative Citation Recommendation". In Proceedings of Open research Areas in Information Retrieval Conference (OAIR 2013). ACM Press.

  9. Ruocco, M. and H. Ramampiaro, (2012), "Exploratory Analysis on Heterogeneous Tag-Point Patterns for Ranking and Extracting Hot-Spot Related Tags", in Proceedings of the 5th ACM SIGSPATIAL International Workshop on Location-Based Social Networks (LBSN 2012), ACM Press.

Multimedia information retrieval focusing on social media

The wide spread of low cost digital cameras an mobile phones has made it easy for people to share their photos on the web. This has resulted in an explosion of the use of web-based photo sharing systems and other social media such as Flickr, Facebook, Twitter and Panoramio. As part of the Contetx-Aware Image Management (CAIM) project, my research focuses on addressing the challenges due to the amount of available photos, and thus recognizing the necessity of providing tools to efficiently retrieve the available data. In cooperation with my PhD student, Massimiliano Ruocco, I have developed new approaches to deal with the challenges with image retrieval on the web. Our approaches include:

  • Developing efficient search and retrieval methods for image contexts connected to image annotations and metadata

  • Developing techniques to restrict the search spaces through the use of techniques from text mining and natural language processing as well as multimedia information retrieval

  • Developing techniques for automatic generation of image annotations

Relevant Publications

  1. M. Ruocco and H. Ramampiaro, (2015), "Geo-Temporal Distribution of Tag Terms for Event-Related Image Retrieval". In Information Processing & Management Journal (IPM), 51(1), pp. 92-110. Elsevier. ISSN: 0306-4573. Impact Factor: 1.069 (2013). (Published online Sept. 2014).

  2. Ruocco, M. and H. Ramampiaro, (2014), In Multimedia Tools and Applications Journal (MTAP), 70(1), pp. 55-88. Springer. ISSN: 1380-7501. Impact Factor: 1.058 (2013). (Published online May 2012).

  3. M. Ruocco and H. Ramampiaro, (2013), "Event-Related Image Retrieval: Exploring Geographical and Temporal Distribution of User Tags". In International Journal of Multimedia Information Retrieval (JMIR), 2(4), pp 273-288. Springer. ISSN: 2192-6611.

  4. M. Ruocco and H. Ramampiaro, (2013), "Exploring Temporal Proximity and Spatial Distribution of Terms in Web-based Search of Event-Related Images". In Proc. of the 24th ACM Conference on Hypertext and Social Media (Hypertext 2013). ACM Press. (To Appear).

  5. M. Ruocco and H. Ramampiaro, (2012), "Exploratory Analysis on Heterogeneous Tag-Point Patterns for Ranking and Extracting Hot-Spot Related Tags". In Proc. of the 5th ACM SIGSPATIAL International Workshop on Location-Based Social Networks (LBSN) 2012. ACM Press.

  6. M. Ruocco and H. Ramampiaro, (2010), "Event Clusters Detection on Flickr Images using a Suffix-Tree Structure". In Proc. of The IEEE International Symposium on Multimedia (ISM2010), Taichung, Taiwan, Dec. 13-15, 2010. IEEE Computer Society.

Information retrieval for Biomedicine

The continuous increase in the amount of available biomedical information has resulted in a higher demand on biomedical information retrieval (IR) systems. While their use has helped researchers in the field to stay updated on recent literature, many of the existing search systems tend to be either too restrictive (returning results with a low recall) or too broad (finding results with a low precision). For this reason, there is still a need to improve existing search systems, especially with respect to retrieval performance, in order to improve their precision and recall. With this as a starting point, I initiated the research project called BioTracer to investigate on the possibility for the development of methods and framework for optimized biomedical information retrieval. The main focus has been on finding unified ways to support the retrieval of biomedical information, while at the same time taking into account all the challenges connected to this type of information. Such challenges range from dealing with heterogeneous and inconsistent information to dealing with a constant increase in sizes. Our research on this topic has so far led to several published papers that I list below.

Relevant Publications:

  1. H. Ramampiaro and C. Li, (2011), "Supporting BioMedical Information Retrieval: The BioTracer Approach". In Transactions on Large-Scale Data- and Knowledge-Centered Systems 4, Vol. 6990, pp. 73-94, 2011. Springer.

  2. H. Ramampiaro (2010), "BioMedical Information Retrieval: The BioTracer Approach", In Proc. of 1st International Conference on Information Technology in Bio- and Medcial Informatics (ITBAM 2010). Vol. 6266. pp. 143-157. LNCS Springer Verlag.

  3. Y. H. Chen, H. Ramampiaro, A. Lægreid and R. Sætre, (2007), "ProtIR prototype: abstract relevance for Protein-Protein Interaction in BioCreAtIvE2 Challenge, PPI-IAS subtask". In Proceedings of the Second BioCreative Challenge Evaluation Workshop.

  4. V. Beisvag, F. Jünge, H. Bergum, L. Jølsum, S. Lydersen, C.C. Günther, H. Ramampiaro, M. Langaas, A.K. Sandvik, and A. Lægreid, (2006), "GeneTools: application for functional annotation and statistical hypothesis testing". In BMC Bioinformatics, 7(270). BioMed Central.

  5. V. Beisvag, F. Jünge, H. Bergum, C.C. Günther, M. Langaas, H. Ramampiaro, and A. Lægreid, (2005), "GeneTools: Resources for Functional Annotations". In 8th International Meeting of the Microarray Gene Expression Data Society.

Search in large data collections

In this research stream, my main interests are on proximity string search in large collections. In particular, the current focus is on search of sequences in large data collections of DNA sequences. Since its discovery, DNA has been subject to intensive research. Technological advances have made DNA sequencing faster and more available, which has gone from being a manual task to being highly automated. As a result, many projects aiming at sequencing DNA were initiated. All these efforts have led to a vast amount of DNA sequences, which have called for high performance search systems. Several challenges have been faced due to the amount of data, and despite the existence of many solutions, the necessity of new and improved methods for searching in DNA is still evident. One approach that we are currently investigating is the use of methods from content-based images retrieval to index and retrieve DNA sequences. Though still in its early stage, preliminary results from this work have already been published in an international conference. The reviewers have characterized this work as original and innovative. Our hope is to provide an approach that can supplement today's standard batch solutions - such as those using BLAST - with the ability to search for DNA sequences in an interactive fashion. For this reason, our future work in this area will focus on further investigating techniques to optimize the storage and indexing of large sequences to make them feasible to search in interactive environments.

Relevant Publications

  1. H. Ramampiaro and A. Grande, (2011), "DNA Sequence Search Using Content-Based Image Search Approach". In Proc. of 5th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2011). Springer Verlag. Advances in Intelligent and Soft Computing, 2011, Volume 93/2011, 191-199.

  2. V. Beisvag, F. Jünge, H. Bergum, L. Jølsum, S. Lydersen, C.C. Günther, H. Ramampiaro, M. Langaas, A.K. Sandvik, and A. Lægreid, (2006), "GeneTools: application for functional annotation and statistical hypothesis testing". In BMC Bioinformatics, 7(270). BioMed Central.

Advanced database support for CSCW

The advances of computer and network technology have undoubtedly changed the way we carry out our work. Much work is performed in teams distributed over networks, where groups get together to have their work done without strict organizational structure. As a result, the induced work environments are continuously changing and heterogeneous, resulting in challenges on providing optimal support for information sharing. Thus the goal of this work is to provide transaction support for cooperative work environments, focusing on data and information sharing - i.e., providing suitable mechanisms to manage concurrent access to shared resources. To address the challenges as a result of the dynamic and heterogeneous nature of cooperative work, we developed a new framework that allows us to adapt database transactions to both suit different situations, and at the same time being modifiable, following changes in the actual environment while the work is being performed. The main contributions has thus been a new method allowing adaptable transactional support.

This area was one of the main research areas during my work with my doctoral thesis. My current main interest in this area is managing sharing of data and information in more non-traditional cooperative environments, such as social media.

Relevant Publications

  1. H. Ramampiaro, (2006), "Supporting Collborative Mobile Applications using Adaptable Transactional Framework". In IEEE Proceedings of 2nd International Conference on Collaborative Computing, Atlanta, GA, USA. IEEE.

  2. A.I. Wang, C.F Sørensen, H.N. Le, H. Ramampiaro, R. Conradi and M. Nygård, (2005), "Using the MOWAHS Characterisation Framework for Development of Mobile Work Applications". In Proceedings of the 6th International Conference on Product Focused Software Process Improvement (PROFES 2005). LNCS Springer Verlag.

  3. H.N. Le, M. Nygård and H. Ramampiaro, (2004), "A Locking Model for Mobile Databases in Mobile Environments". In Proceedings of the International Conference on Databases and Applications 2004, Innsbruck. ACTA Press.

  4. H. Ramampiaro, (2004), "Transactional Support for Cooperative Work: Using Mobile Agents in CAGISTrans". In Proceedings of the International Conference on Parallel and Distributed Systems (PDCS 2004), MIT Cambridge. ACTA Press.

  5. H. Ramampiaro and M. Nygård, (2004), "CAGISTrans: Providing adaptable transactional support for cooperative work - An Extended Treatment". In Information Technology & Management (ITM) Journal, Vol. 5, no. 1-2, pp. 23-64. Kluwer Academic Publisher.

  6. H. Ramampiaro, A.I. Wang, C.F Sørensen, H.N. Le, R. Conradi and M. Nygård , (2003), "Requirement Indicators for Mobile Work: The MOWAHS Approach". In Proceedings of the International Symposia on Applied Informatics (AI2003), Innsbruck. ACTA Press.

  7. H. Ramampiaro and M. Nygård, (2002), "Supporting customisable transactions for cooperative work: An experience paper". In Proceedings of the 2002 Western Multi conference (WMC 2002) - Collaborative Technologies Symposium 2002 (CTS 2002), San Antonio. ISCA.

  8. C.F Sørensen, A.I. Wang, H.N. Le, H. Ramampiaro, M. Nygård and R. Conradi, (2002), "The MOWAHS Characterisation Framework for Mobile Work". In Proceedings of the International Symposia on Applied Informatics (AI2002), Innsbruck. ACTA Press.

  9. H. Ramampiaro, (2001), "CAGISTrans: Adaptable Transactional Support for Cooperative Work". Norges teknisk- naturvitenkapelig universitet (NTNU), Dr.Ing. Thesis. NTNU 2001:94, IDI-nr. 6/2001.

  10. H. Ramampiaro and M. Nygård, (2001), "CAGISTrans: A transactional framework for cooperative work". In Proceedings of the 14th International Conference on Parallel and Distributed Computing Systems (PDCS 2001), pages 43-50, Dallas. ISCA.

  11. H. Ramampiaro and M. Nygård, (2001), "CAGISTrans: Providing adaptable transactional support for cooperative work". In Proceedings of the 6th INFORMS Conference on Information Systems and Technology (CIST 2001), pages 3 - 29, Florida. INFORM. Selected for publication in the special issue of Information Technology & Management (ITM) Journal.

  12. H. Ramampiaro, A.I. Wang and T. Brasethvik, (2000), "Supporting distributed cooperative work in CAGIS". In Proceedings of 4th International Conference on Software Engineering and Applications (SEA 2000). ACTA Press.

  13. H. Ramampiaro, M. Divitini, S. A. Petersen, (1999), "Agent-based groupware: Challenges for cooperative transaction models". In J. Estublier et. al, editors, Proceedings of the International Process Technology Workshop (IPTW 99). Pages 18-22, Villard de Lens.

  14. H. Ramampiaro and M. Nygård, (1999), "Cooperative database system: A constructive review of cooperative transaction models". In Proceedings of the 1999 International Symposium on Database Application in Non-Traditional Environment (DANTE 99), pages 315-324. IEEE CS Press.