The semantic mismatch between query and document terms—i.e., the semantic gap—is a long-standing problem in Information Retrieval (IR). Two main linguistic features related to the semantic gap that can be exploited to improve retrieval are synonymy and polysemy. Recent works integrate knowledge from curated external resources into the learning process of neural language models to reduce the effect of the semantic gap. However, these knowledge-enhanced language models have been used in IR mostly for re-ranking and not directly for document retrieval. We propose the Semantic-Aware Neural Framework for IR (SAFIR), an unsupervised knowledge-enhanced neural framework explicitly tailored for IR. SAFIR jointly learns word, concept, and document representations from scratch. The learned representations encode both polysemy and synonymy to address the semantic gap. SAFIR can be employed in any domain where external knowledge resources are available. We investigate its application in the medical domain where the semantic gap is prominent and there are many specialized and manually curated knowledge resources. The evaluation on shared test collections for medical literature retrieval shows the effectiveness of SAFIR in terms of retrieving and ranking relevant documents most affected by the semantic gap.

The Precision Medicine (PM) track at the Text REtrieval Conference (TREC) focuses on providing useful precision medicine-related information to clinicians treating cancer patients. The PM track gives the unique opportunity to evaluate medical IR systems using the same set of topics on two different collections: scientific literature and clinical trials. In the paper, we take advantage of this opportunity and we propose and evaluate state-of-the-art query expansion and reduction techniques to identify whether a particular approach can be helpful in both scientific literature and clinical trial retrieval. We present those approaches that are consistently effective in both TREC editions and we compare the results obtained with the best performing runs submitted to TREC PM 2017 and 2018.

This paper introduces the main characteristics of the digital cultural collections that constitute the use cases presently in use in the CULTURA environment. A section on related work follows giving an account on efforts on the management of digital annotations that are pertinent and that have been considered. Afterwards the innovative annotation features of the CULTURA portal for digital humanities are described; those features are aimed at improving the interaction of non-specialist users and general public with digital cultural heritage content. The annotation functions consist of two modules: the FAST annotation service as back-end and the CAT Web front-end integrated in the CULTURA portal. The annotation features have been, and are being, tested with different types of users and useful feedback is being collated, with the overall aim of generalising the approach to diverse document collections and not only the area of cultural heritage.

The Exploration, Navigation and Retrieval of Information in Cultural Heritage Workshop (ENRICH 2013) offers a forum to 1) discuss the challenges and opportunities in Information Retrieval research in the area of Cultural Heritage; 2) encourage collaboration between researchers engaged in work in this specialist area of Information Retrieval, and to foster the formation of a research community; and 3) identify a set of actions which the community should undertake to progress the research agenda. The workshop will foster a new stream of Information Retrieval research and support the design of search tools that can help end-users fully exploit the wonderful Cultural Heritage material that is available across the globe.

The workshop focuses on the three areas of interest to CIKM to discuss how to envisage and design evaluation infrastructures able to store, manage, and make accessible the scientific data and knowledge of interest for advancing the evaluation of information retrieval and access tools.

The paper addresses the problem of representing, managing and exchanging hierarchically structured data in the context of Digital Library (DL) systems in order to enhance the access and exchange DL resources on the Web. We propose the NEsted SeTs for Object hieRarchies (NESTOR) framework, which relies on two set data models — the “Nested Set Model (NS-M)” and the “Inverse Nested Set Model (INS-M)” — to enable the representation of hierarchical data structures by means of a proper organization of nested sets. In particular, we show how NESTOR can be effectively exploited to enhance Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) for better access and exchange of hierarchical resources on the Web.

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.

This work describes the interface design and interaction of a generic annotation service for Digital Library Management Systems (DLMSs), called Digital Library Annotation Service (DiLAS), that has been designed and is currently undergoing development and user test in the framework of the DELOS European Network of Excellence. The objective of DiLAS is to design and develop an architecture and a framework able to support and evaluate a generic annotation service, i.e. a service that can be easily used into different DLMSs enhancing their User Interfaces (UIs) in order to offer to Digital Library (DL) users a set of uniform, user-tested (under certain required conditions), and recognizable functionalities. Copyright 2006 ACM.

No abstract available.

This paper presents searching approaches and user interface capabilities of DUO, an Online Public Access Catalogue (OPAC) designed to permit the users of three Universities of the Northeast of Italy different subject searching accesses to the co-operative multi-disciplines library catalogue database.The co-operative catalogue database is managed by one of the software systems developed under the italian national project for library automation: the SBN project. Since the SBN database has not been designed to be efficiently accessed for end-user searches, the DUO database has been designed to avoid duplication of the SBN database data and to be usable for making efficient subjects accesses to the catalogue documents. The DUO design choices are presented, in particular the main choice of designing a “virtual” document that corresponds to each SBN document and that has unstructured data usable for subject search purposes.The paper presents a new kind of user-OPAC dialogue that makes available to the user different search approaches and on-line dictionaries. In particular the user during the interaction with the search tool can represent his information needs with the support of interface capabilities that are based on retrieval path history, and words and codes on-line dictionaries.DUO is the first Italian OPAC that has been made openly available to users of universities and research institutions. For this reason, it is also the first time that OPAC log data is going to be collected in Italy. This work mainly intends to make a modern OPAC available to the users of a SBN catalogue database, but it is going to permit also to build up a knowledge on OPAC usage in Italy.

This paper addresses the methodological aspects of designing a semantic association function in a hypertext information retrieval environment and model. Through this function a part of an associative information retrieval model is designed and implemented. Initially the paper provides reference to previous efforts in associative information retrieval and automatic search formulation and re-formulation operations. The semantic association function is a function which belongs to a new functional hypertext information retrieval model that has been previously justified and presented. For this reason, the meaning and aim of the semantic association function are also recalled and reported. The central part of the paper presents motivations and justification for the design and implementation of the semantic association function in an experimental hypertext information retrieval interface as opposed to a traditional online information retrieval system.

This paper introduces an associative information retrieval model based on the two-level architecture proposed in [Agosti et al, 1989a] and [Agostiet al, 1990], andan experimental prototype developed in order to validate the model in a personal computing environment.In the fiist part of the paper, related work and motivations are presented.In the second pert, the model, entitled EXPLICIT, is introduced.EXPLICIT is basedon a two-level architecture which holds the two main parts of the informative resource managed by an information retrieval tool:the collection of documents and the indexing term structure.Theterm structure is managed as a schema of concepts which can be used by the final user as a frame of reference in the query formulation process.llemodel supports theconcurrent use of different schemas of concepts to satisfy information needs of different categories of users.Inthethird part of the paper, the main characteristics of the experimental prototype, named HyperLaw, are presented.

This panel will employ two different interpretations of the phrase “growing up” to address areas of common interest between hypertext and information retrieval researchers. First, the panelists will question whether or not hypertext is “growing up” as a scientific discipline; They will discuss characteristics that separate hypertext research from other related disciplines. Second, the panelists will discuss the problems encountered when a hypertext system “grows up” in size and complexity; They will discuss the very real problems expected when representing and integrating large knowledge bases, accommodating multiple users, and distributing single logical hypertexts across multiple physical sites.