Towards an ontology of ElPub/SciX: a proposal

A proposal is presented for a standard ontology language defined as ElPub/SciX Ontology, based on the content of a web digital library of conference proceedings. This content, i.e., ElPub/SciX documents, aims to provide access to papers presented at the total editions of the International Conference in Electronic Publishing (ElPub). After completing its 10th years in 2006, ElPub/SciX is now a comprehensive repository with over 400 papers. Previous work has been used as a basis to build up the ontology described here. It has been presented at Elpub2004 and it dealt with an Information Retrieval System using Computational Linguistics (SiRILiCo). ElPub/SciX ontology constitutes a lightweight ontology (classes and just some instances) and is the result of two basic procedures. The first one is a syntactic analysis carried out through the Syntactic Parser-VISL. This free tool, based on lingsoft's ENGCG parser, is made available through the Visual Interactive Syntactic Learning, a research and development project at the University of Southern Denmark, Institute of Language and Communication (ISK). The second one, carried out after that, is a semantic analysis (concept extraction) conducted through GeraOnto, an acronym that stands for “generating an ontology”, which extracts the concepts needed in order to build up the ontology. The program has been developed by Gottschalg-Duque, in 2005, in Brazil. The ensuing ontology is then edited via Protégé, a free, open source ontology editor. The motivation to carry out the work reported here came from problems faced during the preparation of a paper to Elpub2006, which aimed to present data about a number of aspects regarding the ElPub/SciX collection. While searching the collection, problems with the lack of standardization of authors and institutions names and the non-existence of any control of keywords had been identified. Such problems seem to be related to an apparent absence of “paper preparation” before entering into the SciX database. Lack of preparation, in turn, has brought about the desire of finding a solution, which is expected to support the work of those interested in searching the collection to retrieve information. ElPub/SciX ontology, therefore, is seen as that helping solution to support ElPub information retrieval

An Efficient approach for finding the essential experts in Digital Library

Name ambiguity is a special case of identity uncertainty where one person can be referenced by multiple name variations in different situations or even share the same name with other people. In this paper, we focus on Nam e Disambiguation problem. When non - unique values are used as the identifier of Entities, due to their homonym, confusion can occur. In particular, when (part of ) "names" of entities are used as their identifier, the problem is often referred to as the name disambiguation problem, where goal is to sort out the erroneous entities due to name homonyms (e.g., if only last name is used as the identifier, one cannot distinguish "Vannevar Bush" from "George Bush"). We formalize the problem in a unified probabilistic framework and propose a algorithm for parameter estimation. We use a dynamic approach for estimating the number of people K and for finding the experts in digital library by counting the number of accesses of the paper

Harnessing Historical Corrections to build Test Collections for Named Entity Disambiguation

Matching mentions of persons to the actual persons (the name disambiguation problem) is central for several digital library applications. Scientists have been working on algorithms to create this matching for decades without finding a universal solution. One problem is that test collections for this problem are often small and specific to a certain collection. In this work, we present an approach that can create large test collections from historical metadata with minimal extra cost. We apply this approach to the DBLP collection to generate two freely available test collections. One collection focuses on the properties of defects and one on the evaluation of disambiguation algorithms.Comment: Preprint of a paper accepted at TPDL 201

Bayesian Non-Exhaustive Classification A Case Study: Online Name Disambiguation using Temporal Record Streams

The name entity disambiguation task aims to partition the records of multiple real-life persons so that each partition contains records pertaining to a unique person. Most of the existing solutions for this task operate in a batch mode, where all records to be disambiguated are initially available to the algorithm. However, more realistic settings require that the name disambiguation task be performed in an online fashion, in addition to, being able to identify records of new ambiguous entities having no preexisting records. In this work, we propose a Bayesian non-exhaustive classification framework for solving online name disambiguation task. Our proposed method uses a Dirichlet process prior with a Normal * Normal * Inverse Wishart data model which enables identification of new ambiguous entities who have no records in the training data. For online classification, we use one sweep Gibbs sampler which is very efficient and effective. As a case study we consider bibliographic data in a temporal stream format and disambiguate authors by partitioning their papers into homogeneous groups. Our experimental results demonstrate that the proposed method is better than existing methods for performing online name disambiguation task.Comment: to appear in CIKM 201

Name Disambiguation from link data in a collaboration graph using temporal and topological features

In a social community, multiple persons may share the same name, phone number or some other identifying attributes. This, along with other phenomena, such as name abbreviation, name misspelling, and human error leads to erroneous aggregation of records of multiple persons under a single reference. Such mistakes affect the performance of document retrieval, web search, database integration, and more importantly, improper attribution of credit (or blame). The task of entity disambiguation partitions the records belonging to multiple persons with the objective that each decomposed partition is composed of records of a unique person. Existing solutions to this task use either biographical attributes, or auxiliary features that are collected from external sources, such as Wikipedia. However, for many scenarios, such auxiliary features are not available, or they are costly to obtain. Besides, the attempt of collecting biographical or external data sustains the risk of privacy violation. In this work, we propose a method for solving entity disambiguation task from link information obtained from a collaboration network. Our method is non-intrusive of privacy as it uses only the time-stamped graph topology of an anonymized network. Experimental results on two real-life academic collaboration networks show that the proposed method has satisfactory performance.Comment: The short version of this paper has been accepted to ASONAM 201

ScriptLattes: an open-source knowledge extraction system from the Lattes platform

The Lattes platform is the major scientific information system maintained by the National Council for Scientific and Technological Development (CNPq). This platform allows to manage the curricular information of researchers and institutions working in Brazil based on the so called Lattes Curriculum. However, the public information is individually available for each researcher, not providing the automatic creation of reports of several scientific productions for research groups. It is thus difficult to extract and to summarize useful knowledge for medium to large size groups of researchers. This paper describes the design, implementation and experiences with scriptLattes: an open-source system to create academic reports of groups based on curricula of the Lattes Database. The scriptLattes system is composed by the following modules: (a) data selection, (b) data preprocessing, (c) redundancy treatment, (d) collaboration graph generation among group members, (e) research map generation based on geographical information, and (f) automatic report creation of bibliographical, technical and artistic production, and academic supervisions. The system has been extensively tested for a large variety of research groups of Brazilian institutions, and the generated reports have shown an alternative to easily extract knowledge from data in the context of Lattes platform. The source code, usage instructions and examples are available at http://scriptlattes.sourceforge.net/.Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)CNPqFAPES