REPORTon
ACM SIGIR WORKSHOP ON MATHEMATICAL/FORMAL
METHODS IN INFORMATION RETRIEVAL
MF/IR 2002
Tampere, Finland
August 12-15, 2002
Sandor Dominich
Mounia Lalmas
C. J. "Keith" van Rijsbergen

Introduction
The previous two MF/IR workshops (ACM SIGIR 2000 MF/IR 2000, Athens,Greece, and ACM SIGIR 2001 MF/IR 2001, New Orleans, USA) showed thatthe mathematical/formal results achieved in Information Retrieval (IR) could
be organized into a coherent theoretical framework, that they brought newknowledge to IR, and that mathematical/formal research in IR can stand as a
specialized research area of IR. Therefore the purpose of the MF/IR 2002,
which was the third in row, workshop was, on the one hand, to continue andenhance the results obtained so far, and on the other hand, to present, discuss,analyze, integrate the newer/newest results. MF/IR 2002 also aimed atpromoting discussion and interaction among those with theoretical andapplicative research interests in mathematical/formal aspects of Information
Retrieval, and also at being a forum for the presentation of both theoretical andapplicative results (e.g., foundational issues; description and/or integration ofmodels; retrieval applications; mathematical/formal techniques, properties andstructures in IR; existing and/or new theories and theoretical aspects).
The following areas were addressed: Information Retrieval, Information
Filtering, Information, Mining, Indexing and Retrieval, Hypermedia, World
Wide Web Retrieval, Digital Libraries, Evaluation, Human Computer
Interaction, User Modeling, Semantic Web and Ontologies, where the differententities involved (e.g., documents, queries, indexing, retrieval, relevance,effectiveness, users, etc.) were modeled using any of, but not necessarily
limited to, the following approaches: Classical Sets, Fuzzy Sets, Rough Sets,Vectors, Linear Space, Similarity Functions, Probability, Theory ofUncertainty, Functional Analysis, Algebra, Topology, Metric Spaces,
Euclidean Geometry, Non-Euclidean Geometries, Boolean Logic, Nonstandard Logics, Fuzzy Logic, Quantum Logic, Matroid Theory, Graph
Theory.

Papers
The event began with an opening talk given by C.J. van Rijsbergen entitled"The geometry of information retrieval". Van Risjbergen argued that basic
concepts of quantum mechanics (states, observables, measurement) can beused to build a consistent theoretical  geometrical  framework forinformation retrieval. Probability can be derived from the geometry of thespace, retrieval can be formally modeled using projection whereas relevance as
an operator. Whether practical applications can be derived, or feedback andentanglement modeling can be treated within this geometric view are openquestions.
The event continued with papers presentation as follows.
S. Robertson (Microsoft Research Cambridge, UK): On Bayesian models andevent spaces in information retrieval.
Robertson discussed the issue of event spaces in probabilistic models.
After arguing that the basic relationship to compute conditional probabilities
can only be applied correctly to events that belong to the same probability
space, Robertson concluded that the Robertson and Sparck-Jones [1975]
model, denoted briefly by RSJ was not equivalent with the simple language
model as claimed by Lafferty and Zhai (LZ) in a recent paper. The event spaceof RSJ is the space of documents, but it is not clear what should be taken as
event space in the language model. The LZ model operates with crossproducts of texts of queries and documents, not with events.

B. Thorsten (Palo Alto Research Center, USA): Test data likelihood for PLSAmodels.
The Probabilistic Latent Semantic Analysis (PLSA) model is fitted to a
training corpus by an Expectation Maximization (EM) algorithm, which lacks
the ability to handle unseen documents correctly and does not treat theundefined numeric case null is divided by null. Thorsten proposed an enhanced
EM algorithm to solve this problem, and tested it on the MED collection withsuperior results.
Lee, C., and Lee, G.G. (Pohang Univresity, Korea): Probabilistic informationretrieval model for dependency structured indexing system.
The Authors propose a method to incorporate term dependences into
the probabilistic model. A structural indexing system is adapted to the 2Poisson model, which consists of a dependency parse tree and Chow
expansion. Experiments performed on the ETRI-KEMONG collection inKorean. Both the documents and queries were parsed and terms were extracted.
Performance was evaluated by average precision. The results obtained weremodest.
Dominich, S. (University of Veszprem, Hungary): Paradox-free formal
foundation of vector space model.
The view that documents and queries belong to the same linear spaceyields well-known paradoxes. To overcome them, Dominich suggests thatdocuments should form a probability space, the query is not included. As anoteworthy property it can be shown that the similarity measures reduce thequantity of the Shannon information assigned to it. Experiments are reported toillustrate this.
Goth, J. (University of Veszprem, Hungary): Hyperbolic information retrieval.
Goth investigates the possibility to use the Cayley-Klein hyperbolic
geometry in the vector space model, and defines the hyperbolic information
retrieval model (HIR). It is shown that the usual cosine measure and the new
hyperbolic measure preserve the ranking of documents, which is illustrated
with experiments.

Nie, J-Y, and Jin, F. (University of Montreal, Canada): Integrating logicaloperators in query expansion in vector space model.
Nie and Jin proposed that query expansion in the vector space model
should mean the inclusion of terms into the original query that are alternative
expressions of the original terms rather than additional ones. This can beachieved by OR-ing the expansion terms with the query terms. The expanded
query is evaluated using a fuzzy set based definition of OR. The method wastested on the AP collection with good results.
Chang, Y., Choi, I., Choi, J., Kim, M., (Ajou University, Korea), andRaghavan, V.V. (University of Louisiana at Lafayette, USA: Conceptual
retrieval based on feature clustering of documents.
The Authors propose a method to construct query concepts using thedocuments. Features are identified and extracted from documents using
summarization techniques in vector format, they are then clustered intoprimitive concepts. The top ten most similar concepts to the initial query areused to generate DNFs, of which the one most similar to the query is linearly
combined with the query; this is the used for retrieval. Experiments arereported using TREC-1 with good results.
Plachouras, V., and Ounis, I. (University of Glasgow, UK): Query-biased
combination of evidence on the Web.
Plachouras and Ounis propose a query enhancement technique. A query
scope is defined as a function of the scope of its terms using Wordnet which isviewed in two different ways: as a lattice and as independent terms. These twoviews are combined using Dempster-Shafer's theory of evidence. Experiments
are reported using TREC10, they show that the proposed method doe snot
outperform previous ones.
Hill, S.I., Zaragoza, H. (University of Cambridge, UK), Herbrich, R., andRayner, P.J.W. (Microsoft Research Cambridge,UK): Average precision andthe problem of generalization.
The Authors suggest a bound for average precision based on
McDiarmid bounds, and show that in this way the deviation of observedprecision from its true value can be estimated. Thus, they argue, a learningtheory-based treatment of information retrieval can be built.
Joachims, T. (Cornell University, USA): Evaluating retrieval performanceusing clickthrough data.
Joachims suggests a practical method, which is also theoreticallyanalyzed, to evaluate Web retrieval functions using clickthrough data.
Experiments were conducted using Google, MSNSearch and a Default
strategy, the results are promising but still need analysis.
Friburger, N., and Maurel, D. (Informatics Laboratory Tours, France): Textual
similarity based on proper names.
Friburger and Maurel propose a method to extract proper names fromtexts using a dictionary and automaton model. A piece of text is represented asa vector of its words and as a vector of its proper names (the IDF weighting
scheme is used). The similarity between two texts is defined as a linear
combination of the similarities (dot product) of corresponding words vectors
and proper names vectors. Experiments are reported using the AMARYLLIS
collection. Extensive experiments are reported and discussed.
Kim, H. (Electronics and Telecommunication Research Institute, Korea): The
influence of choice of record field on retrieval performance for bibliographicdatabase.
Kim reports on experiments conducted to investigate how the choice ofrecord fields influence retrieval performance. Query terms were generated
automatically using the INSPEC bibliographic and different fields separately:
abstract, anywhere, descriptor, identifier, subject, title. Performance wasevaluated using the D measure. The experiments showed that perfromance issensitive to which field is selected, and the 'title' field yielded the best results.

Discussion, conclusion
Due to the high number of papers, but in order to allow for maximum
interaction, each presentation was scheduled for 20 minutes including

questions. A 35 minutes discussion allowed further interaction betweenparticipants.
The following more important questions, ideas and views were raised(the number in brackets indicates the sequence of talk)• Can a link be made between probability theory and possibility theory as
regards the probabilistic model? [2]• On what basis can we made the assumption that Σp < 1? [3]• The formulation of the vector space model as an IDO (informationdecreasing operator) was found to be a nice idea. [5]• The use of fuzzy sets theory based formulas needs more justification, also
their effect on rare and common terms. [7]• More should have been said about the scaling up of the method proposed.
[8]• More experimentation is needed to test the generalization proposed. [10]• More should have been said about the experiments (What articles havebeen clustered? What was the size of the collection used?) [12]The MF/IR 2001 organisers were: Sandor Dominich (University ofVeszprem, Hungary), Mounia Lalmas (Queen Mary, University of London,England, U.K.), and Keith van Rijsbergen (University of Glasgow, Scotland,U.K.), who, on behalf of MF/IR 2002 would like to thank the programcommittee for their help and time, and all authors and participants for writing
and presenting papers as well as attending this event. They also would like tothank ACM SIGIR for making this event possible, and the University ofTampere and all local organizers for hosting it.