In this era of ever-increasing computational power, one of the key questions is how we can use such technological progress to our advantage. How can we turn sheer computational power into more intelligent systems? How can we utilize such systems in today's business and economic processes for, e.g., tracking, monitoring, or supporting complex decision making processes? These are questions that inspire my research, yet - paradoxically - I am motivated even more by my doubts as to whether we will ever be able to find definitive answers to questions like these at all. It is the question that drives us.
My name is Alexander Hogenboom and I hold both a Bachelor of Science degree and a cum laude Master of Science degree in Economics and Informatics, with a specialization in Computational Economics. Moreover, I have a PhD degree in Business Intelligence. I am currently affiliated with Erasmus University Rotterdam in the Netherlands as a researcher through a hospitality agreement, after having obtained my PhD degree at this university. I perform my research within the Econometric Institute. Additionally, in the context of my PhD research, I have been affiliated to the research center for Business Intelligence at the Erasmus Research Institute of Management, as well as to Erasmus Studio. Please take a look around on this page in order to find out more about my research endeavors, my publications, as well as my related activities. Welcome to my personal web page!
Research
In general, my research interests all relate to the utilization of methods and techniques from informatics and computer science for facilitating or supporting decision making processes. This has evolved from research related to semantic information systems (mash-ups, query optimization), while obtaining my Bachelor of Science degree, to research in the field of decision support systems (dynamic pricing), while obtaining my Master of Science degree. In the context of my PhD research, my main interests have shifted more towards intelligent systems for information extraction, or more specifically for tracking and monitoring of (economic) sentiment.
PhD Project
The recent turmoil in the financial markets has once again demonstrated how crucial it is for decision makers to identify issues and patterns that matter and to track and predict emerging events. A key element for decision makers to track here is their stakeholders' sentiment. Investor sentiment influences financial markets. Consumer sentiment influences how people spend their money. In general, decision makers have to understand what is going on in their domains and, more specifically, what is driving their stakeholders. What do people think about the economy? About products? Brands? Companies? And where does this sentiment come from?
Nowadays, the Web allows users to produce an ever-growing amount of virtual utterances of opinions in reviews, blogs, tweets, and so on. This yields a massive amount of data, containing traces of valuable information - people's sentiment with respect to products, brands, etcetera. This information can be extracted from textual data by means of sentiment analysis techniques. Typically, the goal of such techniques is to (semi-)automatically determine the polarity of natural language texts.
An intuitive approach here would involve scanning a text for cues signaling its polarity, e.g., positive or negative words. However, when doing so, we may be ignoring important information: the information conveyed by structural aspects of a piece of natural language text. For instance, a conclusion may play a different role in conveying the overall sentiment of a text than a piece of contrasting information does.
Therefore, the goal of my PhD research project was to advance the state-of-the-art of sentiment mining by developing and utilizing models, methods, and algorithms for harvesting the information conveyed by structural aspects of natural language text. This research was linked to the Argumentation Discovery in Economics Literature project of the Erasmus Research Institute of Management. This work has been carried out in the context of the Semantic Scholarly Publishing project of Erasmus Studio as well. Last, I have also performed my research in the context of the COMMITInfiniti project on Information Retrieval for Information Services, work package three. My promotors were Uzay Kaymak and Franciska de Jong, whereas Flavius Frasincar was my daily supervisor.
Developed software and data used in my ongoing research will be made available on this page.
Publications
As my research interests in the area of Business Intelligence vary, my work has led to peer-reviewed publications in various fields. These fields include Information Extraction, Decision Support Systems, and Semantic Information Systems. Some of these publications have been indexed by DBLP and Google Scholar as well.
Sentiment-Based Ranking of Blog Posts using Rhetorical Structure Theory J. Chenlo,
A. Hogenboom, and
D. Losada. In
E. Metais,
F. Meziane,
M. Saraee,
V. Sugumaran, and
S. Vadera, editors,
Natural Language Processing and Information Systems, Eighteenth International Conference on Applications of Natural Language to Information Systems (NLDB 2013), volume 7934 of Lecture Notes in Computer Science, pages 13-24,
Springer,
.
[PDF][Bib][Pub]
A News-Based Approach for Computing Historical Value-at-Risk F. Hogenboom,
M. de Winter,
F. Frasincar, and
A. Hogenboom. In
J. Casillas,
F. Martinez-Lopez, and
J. Corchado, editors,
Management Intelligent Systems, First International Symposium on Management Intelligent Systems (IS-MiS 2012), volume 171 of Advances in Intelligent Systems and Computing, pages 283-292,
Springer,
.
[PDF][Bib][Pub]
A Linguistic Approach for Semantic Web Service Discovery J. Sangers,
F. Frasincar,
F. Hogenboom,
A. Hogenboom, and
V. Chepegin. In
J. Casillas,
F. Martinez-Lopez, and
J. Corchado, editors,
Management Intelligent Systems, First International Symposium on Management Intelligent Systems (IS-MiS 2012), volume 171 of Advances in Intelligent Systems and Computing, pages 131-142,
Springer,
.
[PDF][Bib][Pub]
A Statistical Approach to Star Rating Classification of Sentiment A. Hogenboom,
F. Boon, and
F. Frasincar. In
J. Casillas,
F. Martinez-Lopez, and
J. Corchado, editors,
Management Intelligent Systems, First International Symposium on Management Intelligent Systems (IS-MiS 2012), volume 171 of Advances in Intelligent Systems and Computing, pages 251-260,
Springer,
.
[PDF][Bib][Pub]
Towards Cross-Language Sentiment Analysis through Universal Star Ratings A. Hogenboom,
M. Bal,
F. Frasincar, and
D. Bal. In
L. Uden,
F. Herrera,
J. Perez, and
J. Corchado, editors,
Seventh International Conference on Knowledge Management in Organizations (KMO 2012), volume 172 of Advances in Intelligent Systems and Computing, pages 69-79,
Springer,
.
[PDF][Bib][Pub]
Structuring Political Documents for Importance Ranking A. Hogenboom,
M. Jongmans, and
F. Frasincar. In
G. Bouma,
A. Ittoo,
E. Metais, and
H. Wortmann, editors,
Natural Language Processing and Information Systems, Seventeenth International Conference on Applications of Natural Language to Information Systems (NLDB 2012), volume 7337 of Lecture Notes in Computer Science, pages 745-750,
Springer,
.
[PDF][Bib][Pub]
Event-Based Historical Value-at-Risk F. Hogenboom,
M. de Winter,
M. Jansen,
A. Hogenboom,
F. Frasincar, and
U. Kaymak. In
IEEE Computational Intelligence for Financial Engineering and Economics 2012 (CIFEr 2012), pages 164-170,
IEEE,
.
[PDF][Bib][Pub]
Semantics-Based Financial Event Detection F. Hogenboom,
A. Hogenboom, and
F. Frasincar. In
T. Demeester,
J. Deleu,
L. Mertens,
D. Plaetinck,
A. de Moor,
T. Hoang,
T. Wauters,
C. Develder,
B. Vermeulen, and
P. Demeester, editors,
Twelfth Dutch-Belgian Information Retrieval Workshop (DIR 2012), pages 71-72,
.
[PDF][Bib]
Analyzing Sentiment while Accounting for Negation Scope and Strength A. Hogenboom,
P. van Iterson,
B. Heerschop,
F. Frasincar, and
U. Kaymak. In
P. de Causmaecker,
J. Maervoet,
T. Messelis,
K. Verbeeck, and
T. Vermeulen, editors,
Twenty-Third Benelux Conference on Artificial Intelligence (BNAIC 2011), pages 395-369,
Nevelland,
.
[PDF][Bib][Pub]
Polarity Analysis of Texts using Discourse Structure B. Heerschop,
F. Goossen,
A. Hogenboom,
F. Frasincar,
U. Kaymak, and
F. de Jong. In
B. Berendt,
A. de Vries,
W. Fan,
C. Macdonald,
I. Ounis, and
I. Ruthven, editors,
Twentieth ACM Conference on Information and Knowledge Management (CIKM 2011), pages 1061-1070,
ACM,
.
[PDF][Bib][Pub]
Sentiment Analysis with a Multilingual Pipeline D. Bal,
M. Bal,
A. van Bunningen,
A. Hogenboom,
F. Hogenboom, and
F. Frasincar. In
A. Bouguettaya,
M. Hauswirths, and
L. Liu, editors,
Web Information System Engineering, Twelfth International Conference on Web Information System Engineering (WISE 2011), volume 6997 of Lecture Notes in Computer Science, pages 129-142,
Springer,
.
[PDF][Bib][Pub]
Detecting Economic Events Using a Semantics-Based Pipeline A. Hogenboom,
F. Hogenboom,
F. Frasincar,
U. Kaymak,
O. van der Meer, and
K. Schouten. In
A. Hameurlain,
S. Liddle,
K. Schewe, and
X. Zhou, editors,
Database and Expert Systems, Twenty-Second International Conference on Database and Expert Systems Applications (DEXA 2011), volume 6860 of Lecture Notes in Computer Science, pages 440-447,
Springer,
.
[PDF][Bib][Pub]
Sentiment Lexicon Creation from Lexical Resources B. Heerschop,
A. Hogenboom, and
F. Frasincar. In
W. Abramowicz,
W. van der Aalst,
J. Mylopoulos,
M. Rosemann,
M. Shaw, and
C. Szyperski, editors,
Business Information Systems, Fourteenth International Conference on Business Information Systems (BIS 2011), volume 87 of Lecture Notes in Business Information Processing, pages 185-196,
Springer,
.
[PDF][Bib][Pub]
Accounting for Negation in Sentiment Analysis B. Heerschop,
P. van Iterson,
A. Hogenboom,
F. Frasincar, and
U. Kaymak. In
C. Boscarino,
K. Hofmann,
V. Jijkoun,
E. Meij,
M. de Rijke, and
W. Weerkamp, editors,
Eleventh Dutch-Belgian Information Retrieval Workshop (DIR 2011), pages 38-39,
.
[PDF][Bib][Pub]
Analyzing Sentiment in a Large Set of Web Data while Accounting for Negation B. Heerschop,
P. van Iterson,
A. Hogenboom,
F. Frasincar, and
U. Kaymak. In
E. Mugellini,
P. Szczepaniak,
M. Pettenati, and
M. Sokhn, editors,
Advances in Intelligent Web Mastering - 3, Seventh Atlantic Web Intelligence Conference (AWIC 2011), volume 86 of Advances in Intelligent and Soft Computing, pages 195-205,
Springer,
.
[PDF][Bib][Pub]
SPEED: A Semantics-Based Pipeline for Economic Event Detection F. Hogenboom,
A. Hogenboom,
F. Frasincar,
U. Kaymak,
O. van der Meer,
K. Schouten, and
D. Vandic. In
J. Parsons,
M. Saeki,
P. Shoval,
C. Woo, and
Y. Wand, editors,
Conceptual Modeling - ER 2010, Twenty-Ninth International Conference on Conceptual Modeling (ER 2010), volume 6412 of Lecture Notes in Computer Science, pages 452-457,
Springer,
.
[PDF][Bib][Pub]
Mining Economic Sentiment using Argumentation Structures A. Hogenboom,
F. Hogenboom,
U. Kaymak,
P. Wouters, and
F. de Jong. In
J. Trujillo,
G. Dobbie,
H. Kangassalo,
S. Hartmann,
M. Kirchberg,
M. Rossi,
I. Reinhartz-Berger,
E. Zimanyi, and
F. Frasincar, editors,
Advances in Conceptual Modeling - Applications and Challenges, Seventh International Workshop on Web Information Systems Modeling (WISM 2010) at the Twenty-Ninth International Conference on Conceptual Modeling (ER 2010), volume 6413 of Lecture Notes in Computer Science, pages 200-209,
Springer,
.
[PDF][Bib][Pub]
RCQ-ACS: RDF Chain Query Optimization Using an Ant Colony System A. Hogenboom,
E. Niewenhuijse,
F. Hogenboom, and
F. Frasincar. In
N. Zhong,
Z. Gong,
Y. Cheung,
P. Lingras,
P. Szczepaniak, and
E. Suzuki, editors,
2012 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2012), pages 74-81,
IEEE,
.
[PDF][Bib][Pub]
RCQ-GA: RDF Chain Query Optimization using Genetic Algorithms A. Hogenboom,
V. Milea,
F. Frasincar, and
U. Kaymak. In
T. Di Noia and
F. Buccafurri, editors,
E-Commerce and Web Technologies, Tenth International Conference on Electronic Commerce and Web Technologies (EC-Web 2009), volume 5692 of Lecture Notes in Computer Science, pages 181-192,
Springer,
.
[PDF][Bib][Pub]
Genetic Algorithms for RDF Query Path Optimization A. Hogenboom,
V. Milea,
F. Frasincar, and
U. Kaymak. In
C. Gueret,
P. Hitzler, and
S. Schlobach, editors,
First International Workshop on Nature Inspired Reasoning for the Semantic Web (NatuReS 2008), pages 16-30,
CEUR-WS,
.
[PDF][Bib][Pub]
QMap: An RDF-Based Queryable World Map F. Hogenboom,
A. Hogenboom,
R. van Gelder,
V. Milea,
F. Frasincar, and
U. Kaymak. In
M. Naaranoja, editor,
Third International Conference on Knowledge Management in Organisations (KMO 2008), volume 151 of Selvityksia Ja Raportteja, pages 99-110,
Vaasan Yliopiston Julkaisuja,
.
[PDF][Bib]
Teaching
The work I have performed has involved some activities other than just performing research as well. Over the years, I have been involved with several courses and I have performed several (co-)supervision activities.
RDF Chain Query Optimization in a Distributed Environment
E. Niewenhuijse (Bachelor's Thesis, February 2013).
Exploiting Rhetorical Structure of Text in Sentiment Analysis for Decision Support
B. Heerschop (Master's Thesis, September 2012).
A Multi-Feature Approach to Sentiment Summarization of Online Conversational Documents
G. Mangnoesing (Bachelor's Thesis, August 2012).
A Linguistic Approach for Searching Economic News
K. Schouten (Master's Thesis, May 2012).
Cross-Language Sentiment Normalization through Interchangeability between Sentiment Analysis and Universal Star Rating
M. Bal (Bachelor's Thesis, July 2011).
Adding Emoticon Semantics to Sentiment Analysis
D. Bal (Bachelor's Thesis, July 2011).
Using IT to Improve Knowledge about Political-Economic Space
M. Jongmans (Master's Thesis, August 2010).
Supporting Multiple Languages in Sentiment Analysis
B. Heerschop (Bachelor's Thesis, August 2010).
Negation Improvements in Sentiment Analysis
P. van Iterson (Bachelor's Thesis, August 2010).
Review Sentiment Categorization Using a 5-Star Scale
F. Boon (Bachelor's Thesis, July 2010).
Other
Besides my research, teaching, and supervision activities, I have spent some of my time on some other work-related activities as well. Some of my efforts have also resulted in honors and awards.
IEEE SMC student travel grant for attending and presenting at the 2011 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2011), Anchorage, Alaska, United States, October 9-12 2011.
IEEE SMC student travel grant for attending and presenting at the 2010 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2010), Istanbul, Turkey, October 10-13 2010.
Honorable Mention Award for paper at the Eleventh International Conference on Electronic Commerce (ICEC 2009), Taipei, Taiwan, August 12-15 2009.
TAC 2009 student travel grant for attending and presenting at the Workshop on Trading Agent Design and Analysis (TADA 2009) at the Twenty-First International Joint Conference on Artificial Intelligence (IJCAI 2009), Pasadena, California, United States, July 11-17 2009.
Contact
AlexanderHogenboom, PhD.
Researcher
Econometric Institute Erasmus School of Economics Erasmus University Rotterdam
Visiting:
Burgemeester Oudlaan 50 3062 PARotterdam The Netherlands