Mark James Carman

Senior Lecturer
Caulfield School of Information Technology
Monash University

phone: +61 3 9903 4329

office: H6.46, Monash University Caulfield Campus
900 Dandenong Road, Caulfield East, Victoria

postal address: PO Box 197, Caulfield East, Victoria 3145, Australia

Research Interests and Expertise

Dr. Carman is an expert in Data Science, Data Mining and the analysis of Big Data. His primary research interests are Information Retrieval and Machine Learning. His specific areas of expertise include: His research and interests span theoretical studies (e.g. investigating statistical properties of information retrieval measures), through to practical applications (e.g. technology for assisting police during digital forensic investigations).

Dr. Carman has authored a large number of publications in prestigious venues, including full papers at SIGIR, KDD, IJCAI, CIKM, ECIR, WSDM, HT, CoNLL, EACL, HCOMP and ICDAR, and articles in TOIS, IR, JMLR, ML, PR, JAIR, CS&L, JASIST, DI and CSUR.

Major contributions of his research career have included developing state-of-the-art techniques for:

Research Projects

Dr. Carman is involved in a variety of research projects, some of his recent ones are summarised below.

A Brief Bio (see also CV)

Mark Carman is a senior lecturer at Monash University in Melbourne, Australia. He joined Monash in 2010 after a postdoc at the University of Lugano. He received his PhD from the University of Trento in 2006 having worked at both the Fondazione Bruno Kessler (FBK-IRST) and the Information Sciences Institute (USC-ISI). Mark works primarily in information retrieval, applying and extending statistical machine learning techniques to the modelling of users and user-generated content. He has served on the program committees of many IR/DM conferences (SIGIR, ECIR, KDD, CIKM, EMNLP, AAAI, ACML, etc.) and is an Associate Editor for TOIS.

PhD Students

Graduated: Current:

Publications (see also my Google Scholar page)

The following is a list of selected publications. Please send an if you can't get access to a particular paper.


EIDOS (Efficiently Inducing Definitions for Online Sources) is a system for learning semantic descriptions of online information sources (such as RSS feeds). The descriptions are used to automatically integrate the sources into (mediator based) information integration systems. A complete description of the purpose and functionality of the system can be found in my thesis. You can also have a look at the slides I presented at my defense. The software can be downloaded from the ISI website. It is royalty-free for research purposes and comes with all the source code. Here is the latest documentation. Feel free to contact me with installation questions.

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