Determining the polarity of postings for discussion search

When performing discussion search it might be desirable to consider non-topical measures like the number of positive and negative replies to a posting, for instance as one possible indicator for the trustworthiness of a comment. Systems like POLAR are able to integrate such values into the retrieval function. To automatically detect the polarity of postings, they need to be classified into positive and negative ones w.r.t.\ the comment or document they are annotating. We present a machine learning approach for polarity detection which is based on Support Vector Machines. We discuss and identify appropriate term and context features. Experiments with ZDNet News show that an accuracy of around 79\%-80\% can be achieved for automatically classifying comments according to their polarity

Towards a geometrical model for polyrepresentation of information objects

The principle of polyrepresentation is one of the fundamental recent developments in the field of interactive retrieval. An open problem is how to define a framework which unifies different as- pects of polyrepresentation and allows for their application in several ways. Such a framework can be of geometrical nature and it may embrace concepts known from quantum theory. In this short paper, we discuss by giving examples how this framework can look like, with a focus on in- formation objects. We further show how it can be exploited to find a cognitive overlap of different representations on the one hand, and to combine different representations by means of knowledge augmentation on the other hand. We discuss the potential that lies within a geometrical frame- work and motivate its further developmen

Exploiting information needs and bibliographics for polyrepresentative document clustering

In this paper we explore the potential of combining the principle of polyrepresentation with document clustering. Our idea is discussed and evaluated for polyrepresentation of information needs as wells as for document-based polyrepresentation where bibliographic information is used as representation. The main idea is to present the user with the highly ranked polyrepresentative clusters to support the search process. Our evaluation suggests that our approach is capable of increasing retrieval performance, but performance varies for queries with a high or low number of relevant documents

Applying Cross-cultural theory to understand users’ preferences on interactive information retrieval platform design

Presented at EuroHCIR 2014, the 4th European Symposium on Human-Computer Interaction and Information Retrieval, 13th September 2014, at BCS London Office, Covent Garden, London.In this paper we look at using culture to group users and model the users’ preference on cross cultural information retrieval, in order to investigate the relationship between the user search preferences and the user’s cultural background. Initially we review and discuss briefly website localisation. We continue by examining culture and Hofstede’s cultural dimensions. We identified a link between Hofstede’s five dimensions and user experience. We did an analogy for each of the five dimensions and developed six hypotheses from the analogies. These hypotheses were then tested by means of a user study. Whilst the key findings from the study suggest cross cultural theory can be used to model user’s preferences for information retrieval, further work still needs to be done on how cultural dimensions can be applied to inform the search interface design

Multi-facet classification of e-mails in a helpdesk scenario

Helpdesks have to manage a huge amount of support requests which are usually submitted via e-mail. In order to be assigned to experts e ciently, incoming e-mails have to be classi- ed w. r. t. several facets, in particular topic, support type and priority. It is desirable to perform these classi cations automatically. We report on experiments using Support Vector Machines and k-Nearest-Neighbours, respectively, for the given multi-facet classi - cation task. The challenge is to de ne suitable features for each facet. Our results suggest that improvements can be gained for all facets, and they also reveal which features are promising for a particular facet

Combining cognitive and system-oriented approaches for designing IR user interfaces

Poster at the AIR workshop 2008, London, Englan

Preliminary study of technical terminology for the retrieval of scientific book metadata records

Books only represented by brief metadata (book records) are particularly hard to retrieve. One way of improving their retrieval is by extracting retrieval enhancing features from them. This work focusses on scientific (physics) book records. We ask if their technical terminology can be used as a retrieval enhancing feature. A study of 18,443 book records shows a strong correlation between their technical terminology and their likelihood of relevance. Using this finding for retrieval yields >+5% precision and recall gains

Identifying the relevance of personal values to e-government portals' success: insights from a Delphi study

Most governments around the world have put considerable financial resources into the development of e-government systems. They have been making significant efforts to provide information and services online. However, previous research shows that the rate of adoption and success of e-government systems vary significantly across countries. It is argued here that culture can be an important factor affecting e- government success. This paper aims to explore the relevance of personal values to the e-government success from an individual user’s perspective. The ten basic values identified by Schwartz were used. A Delphi study was carried out with a group of experts to identify the most relevant personal values to the e-government success from an individual’s point of view. The findings suggest that four of the ten values, namely Self-direction, Security, Stimulation, and Tradition, most likely affect the success. The findings provide a basis for developing a comprehensive e-government evaluation framework to be validated using a large scale survey in Saudi Arabia

On the probabilistic logical modelling of quantum and geometrically-inspired IR

Information Retrieval approaches can mostly be classed into probabilistic, geometric or logic-based. Recently, a new unifying framework for IR has emerged that integrates a probabilistic description within a geometric framework, namely vectors in Hilbert spaces. The geometric model leads naturally to a predicate logic over linear subspaces, also known as quantum logic. In this paper we show the relation between this model and classic concepts such as the Generalised Vector Space Model, highlighting similarities and differences. We also show how some fundamental components of quantum-based IR can be modelled in a descriptive way using a well-established tool, i.e. Probabilistic Datalog

Exploring a Multidimensional Representation of Documents and Queries (extended version)

In Information Retrieval (IR), whether implicitly or explicitly, queries and documents are often represented as vectors. However, it may be more beneficial to consider documents and/or queries as multidimensional objects. Our belief is this would allow building "truly" interactive IR systems, i.e., where interaction is fully incorporated in the IR framework. The probabilistic formalism of quantum physics represents events and densities as multidimensional objects. This paper presents our first step towards building an interactive IR framework upon this formalism, by stating how the first interaction of the retrieval process, when the user types a query, can be formalised. Our framework depends on a number of parameters affecting the final document ranking. In this paper we experimentally investigate the effect of these parameters, showing that the proposed representation of documents and queries as multidimensional objects can compete with standard approaches, with the additional prospect to be applied to interactive retrieval