Nicola Ferro

A formal model of annotations of digital content

This article is a study of the themes and issues concerning the annotation of digital contents, such as textual documents, images, and multimedia documents in general. These digital contents are automatically managed by different kinds of digital library management systems and more generally by different kinds of information management systems. Even though this topic has already been partially studied by other researchers, the previous research work on annotations has left many open issues. These issues concern the lack of clarity about what an annotation is, what its features are, and how it is used. These issues are mainly due to the fact that models and systems for annotations have only been developed for specific purposes. As a result, there is only a fragmentary picture of the annotation and its management, and this is tied to specific contexts of use and lacks-general validity. The aim of the article is to provide a unified and integrated picture of the annotation, ranging from defining what an annotation is to providing a formal model. The key ideas of the model are: the distinction between the meaning and the sign of the annotation, which represent the semantics and the materialization of an annotation, respectively; the clear formalization of the temporal dimension involved with annotations; and the introduction of a distributed hypertext between digital contents and annotations. Therefore, the proposed formal model captures both syntactic and semantic aspects of the annotations. Furthermore, it is built on previously existing models and may be seen as an extension of them.

Annotations in Digital Libraries and Collaboratories – Facets, Models and Usage

This paper presents the results of our study regarding the different facets and ways of using annotations in both digital libraries and collaboratories. This study represents an innovative attempt at gathering methodological tools and synergies from both fields in order to effectively define a comprehensive model for annotations. Thus we propose a conceptual model for annotations in order to develop an annotation service that can be plugged into digital libraries and collaboratories. Finally, starting from our model, we introduce a search strategy for exploiting annotations in order to search and retrieve relevant documents for a user query.

A probabilistic model for stemmer generation

In this paper we will present a language-independent probabilistic model which can automatically generate stemmers. Stemmers can improve the retrieval effectiveness of information retrieval systems, however the designing and the implementation of stemmers requires a laborious amount of effort due to the fact that documents and queries are often written or spoken in several different languages. The probabilistic model proposed in this paper aims at the development of stemmers used for several languages. The proposed model describes the mutual reinforcement relationship between stems and derivations and then provides a probabilistic interpretation. A series of experiments shows that the stemmers generated by the probabilistic model are as effective as the ones based on linguistic knowledge.

Annotations as context for searching documents

This paper discusses how to exploit annotations as a useful context in order to search and retrieve relevant documents for a user query. This paper provides a formal framework which can be useful in facing this problem and shows how this framework can be employed, by using techniques which come from the hypertext information retrieval and data fusion fields.

Annotating illuminated manuscripts: an effective tool for research and education

The aim of the paper is to report the research results of an ongoing project that deals with the exploitation of a digital archive of drawings and illustrations of historic documents for research and educational purposes. According to the results on a study of user requirements, we have designed tools to provide researchers with innovative ways for accessing the digital manuscripts, sharing, and transferring knowledge in a collaborative environment. We have found that the results of scientific research on the relationships between images of manuscripts produced over the centuries can be rendered explicit by using annotations. For this purpose, a taxonomy for linking annotation is introduced, together with a conceptual schema which represents annotations and links them to digital objects

Annotations: Enriching a Digital Library

This paper presents the results of a study on the semantics of the concept of annotation. It specifically deals with annotations in the context of digital libraries. In the light of those considerations, general characteristics and features of an annotation service are introduced. The OpenDLib digital library is adopted as a framework of reference for our ongoing research, so the paper presents the annotations extension to the OpenDLib digital library, where the extension regards both the adopted document model and the architecture. The final part of the paper discusses and evaluates if OpenDLib has the expressive power of representing the presented semantics of annotations.

DelosDLMS - the integrated DELOS digital library management system

DelosDLMS is a prototype of a next-generation Digital Library (DL) management system. It is realized by combining various specialized DL functionalities provided by partners of the DELOS network of excellence. Currently, DelosDLMS combines text and audio-visual searching, offers new information visualization and relevance feedback tools, provides novel interfaces, allows retrieved information to be annotated and processed, integrates and processes sensor data streams, and finally, from a systems engineering point of view, is easily configured and adapted while being reliable and scalable. The prototype is based on the OSIRIS/ISIS platform, a middleware environment developed by ETH Zurich and now being extended at the University of Basel.

A historical and contemporary study on annotations to derive key features for systems design

This paper provides a comprehensive study on annotations by defining their contours and complexity. This work adds a new complementary approach to the usual case and user studies, and also investigates history in order to benefit from previous knowledge and our cultural heritage. This study emphasizes an aspect which has never previously been taken into account: the temporal dimension involved in annotations. Moreover, it discusses both the notion of hypertext between documents and annotations and the idea of annotations as context for documents. The study gives the necessary historical and cultural background to derive a set of key features of annotations that must be taken into account when designing systems that have to support the management of digital annotations on digital contents.

Reproducibility Challenges in Information Retrieval Evaluation

Information Retrieval (IR) is concerned with ranking information resources with respect to user information needs, delivering a wide range of key applications for industry and society, such as Web search engines [Croft et al. 2009], intellectual property, and patent search [Lupu and Hanbury 2013], and many others. The performance of IR systems is determined not only by their efficiency but also and most importantly by their effectiveness, that is, their ability to retrieve and better rank relevant information resources while at the same time suppressing the retrieval of not relevant ones. Due to the many sources of uncertainty, as for example vague user information needs, unstructured information sources, or subjective notion of relevance, experimental evaluation is the only mean to assess the performances of IR systems from the effectiveness point of view. Experimental evaluation relies on the Cranfield paradigm, which makes use of experimental collections, consisting of documents, sampled from a real domain of interest; topics, representing real user information needs in that domain; and relevance judgements, determining which documents are relevant to which topics [Harman 2011]. To share the effort and optimize the use of resources, experimental evaluation is usually carried out in publicly open and large-scale evaluation campaigns at the international level, like the Text REtrieval Conference (TREC)1 in the United States [Harman and Voorhees 2005], the Conference and Labs of the Evaluation Forum (CLEF)2 in Europe [Ferro 2014], the NII Testbeds and Community for Information access Research (NTCIR)3 in Japan and Asia, and the Forum for Information Retrieval Evaluation (FIRE)4 in India. These initiatives produce, every year, huge amounts of scientific data

The Effectiveness of a Graph-Based Algorithm for Stemming

In Information Retrieval (IR), stemming enables a matching of query and document terms which are related to a same meaning but which can appear in different morphological variants. In this paper we will propose and evaluate a statistical graph-based algorithm for stemming. Considering that a word is formed by a stem (prefix) and a derivation (suffix), the key idea is that strongly interlinked prefixes and suffixes form a community of sub-strings. Discovering these communities means searching for the best word splits which give the best word stems. We conducted some experiments on CLEF 2001 test subcollections for Italian language. The results show that stemming improve the IR effectiveness. They also show that effectiveness level of our algorithm is comparable to that of an algorithm based on a-priori linguistic knowledge. This is an encouraging result, particularly in a multilingual context.