Search (290 results, page 1 of 15)

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Abstract

We present a short survey of the literature on indexing and retrieval of mathematical knowledge, with pointers to 72 papers and tentative taxonomies of both retrieval problems and recurring techniques.

Date

22. 2.2017 12:51:57

Type

a

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Source

http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&ved=0CDQQFjAE&url=http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F3131107&ei=HzFWVYvGMsiNsgGTyoFI&usg=AFQjCNE2FHUeR9oQTQlNC4TPedv4Mo3DaQ&sig2=Rlzpr7a3BLZZkqZCXXN_IA&bvm=bv.93564037,d.bGg&cad=rja

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Abstract

The design and architecture of MIaS (Math Indexer and Searcher), a system for mathematics retrieval is presented, and design decisions are discussed. We argue for an approach based on Presentation MathML using a similarity of math subformulae. The system was implemented as a math-aware search engine based on the state-ofthe-art system Apache Lucene. Scalability issues were checked against more than 400,000 arXiv documents with 158 million mathematical formulae. Almost three billion MathML subformulae were indexed using a Solr-compatible Lucene.

Content

Vgl.: DocEng2011, September 19-22, 2011, Mountain View, California, USA Copyright 2011 ACM 978-1-4503-0863-2/11/09

Date

22. 2.2017 13:00:42

Type

a

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Abstract

This paper reports on the second part of an initiative of the authors on researching classification systems with the conceptual model defined by the Functional Requirements for Subject Authority Data (FRSAD) final report. In an earlier study, the authors explored whether the FRSAD conceptual model could be extended beyond subject authority data to model classification data. The focus of the current study is to determine if classification data modeled using FRSAD can be used to solve real-world discovery problems in multicultural and multilingual contexts. The paper discusses the relationships between entities (same type or different types) in the context of classification systems that involve multiple translations and /or multicultural implementations. Results of two case studies are presented in detail: (a) two instances of the DDC (DDC 22 in English, and the Swedish-English mixed translation of DDC 22), and (b) Chinese Library Classification. The use cases of conceptual models in practice are also discussed.

Type

a

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Abstract

This paper presents a test of the validity of using Google Scholar to evaluate the publications of researchers by comparing the premises on which its search engine, PageRank, is based, to those of Garfield's theory of citation indexing. It finds that the premises are identical and that PageRank and Garfield's theory of citation indexing validate each other.

Date

17.12.2013 11:02:22

Type

a

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Abstract

Two new methods for retrieving mathematical expressions using conventional keyword search and expression images are presented. An expression-level TF-IDF (term frequency-inverse document frequency) approach is used for keyword search, where queries and indexed expressions are represented by keywords taken from LATEX strings. TF-IDF is computed at the level of individual expressions rather than documents to increase the precision of matching. The second retrieval technique is a form of Content-Base Image Retrieval (CBIR). Expressions are segmented into connected components, and then components in the query expression and each expression in the collection are matched using contour and density features, aspect ratios, and relative positions. In an experiment using ten randomly sampled queries from a corpus of over 22,000 expressions, precision-at-k (k= 20) for the keyword-based approach was higher (keyword: µ= 84.0,s= 19.0, image-based:µ= 32.0,s= 30.7), but for a few of the queries better results were obtained using a combination of the two techniques.

Date

22. 2.2017 12:53:49

Type

a

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Abstract

The author revisits the development of RDA from its inception in 2005 through to its initial release in 2010. The development effort is set in the context of an evolving digital environment that was transforming both the production and dissemination of information resources and the technologies used to create, store, and access data describing those resources. The author examines the interplay between strategic commitments to align RDA with new conceptual models, emerging database structures, and metadata developments in allied communities, on the one hand, and compatibility with AACR2 legacy databases on the other. Aspects of the development effort examined include the structuring of RDA as a resource description language, organizing the new standard as a working tool, and refining guidelines and instructions for recording RDA data.

Date

17. 5.2016 19:22:40

Type

a

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Abstract

More and more cultural heritage institutions publish their collections, vocabularies and metadata on the Web. The resulting Web of linked cultural data opens up exciting new possibilities for searching and browsing through these cultural heritage collections. We report on ongoing work in which we investigate the estimation of relevance in this Web of Culture. We study existing measures of semantic distance and how they apply to two use cases. The use cases relate to the structured, multilingual and multimodal nature of the Culture Web. We distinguish between measures using the Web, such as Google distance and PMI, and measures using the Linked Data Web, i.e. the semantic structure of metadata vocabularies. We perform a small study in which we compare these semantic distance measures to human judgements of relevance. Although it is too early to draw any definitive conclusions, the study provides new insights into the applicability of semantic distance measures to the Web of Culture, and clear starting points for further research.

Date

26.12.2011 13:40:22

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Abstract

This paper presents a crowd-sourced classification of knowledge organization systems based on open knowledge base Wikidata. The focus is less on the current result in its rather preliminary form but on the environment and process of categorization in Wikidata and the extraction of KOS from the collaborative database. Benefits and disadvantages are summarized and discussed for application to knowledge organization of other subject areas with Wikidata.

Pages

S.15-22

Type

a

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Abstract

In 2016, the University of Waterloo began offering a mediated copyright review and deposit service to support the growth of our institutional repository UWSpace. This resulted in the need to batch import large lists of published works into the institutional repository quickly and accurately. A range of methods have been proposed for harvesting publications metadata en masse, but many technological solutions can easily become detached from a workflow that is both reproducible for support staff and applicable to a range of situations. Many repositories offer the capacity for batch upload via CSV, so our method provides a template Python script that leverages the Habanero library for populating CSV files with existing metadata retrieved from the CrossRef API. In our case, we have combined this with useful metadata contained in a TSV file downloaded from Web of Science in order to enrich our metadata as well. The appeal of this 'low-maintenance' method is that it provides more robust options for gathering metadata semi-automatically, and only requires the user's ability to access Web of Science and the Python program, while still remaining flexible enough for local customizations.

Date

10.11.2018 16:27:22

Type

a

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Abstract

This paper builds on the findings of a workshop held at the 2015 International Conference on Digital Preservation (iPRES), entitled, "Using Open-Source Tools to Fulfill Digital Preservation Requirements" (OSS4PRES hereafter). This day-long workshop brought together participants from across the library and archives community, including practitioners proprietary vendors, and representatives from open-source projects. The resulting conversations were surprisingly revealing: while OSS' significance within the preservation landscape was made clear, participants noted that there are a number of roadblocks that discourage or altogether prevent its use in many organizations. Overcoming these challenges will be necessary to further widespread, sustainable OSS adoption within the digital preservation community. This article will mine the rich discussions that took place at OSS4PRES to (1) summarize the workshop's key themes and major points of debate, (2) provide a comprehensive analysis of the opportunities, gaps, and challenges that using OSS entails at a philosophical, institutional, and individual level, and (3) offer a tangible set of recommendations for future work designed to broaden community engagement and enhance the sustainability of open source initiatives, drawing on both participants' experience as well as additional research.

Date

28.10.2016 18:22:33

Type

a

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Abstract

This is an edited collection of 39 original papers and as many commentaries and replies. The target papers and replies were written by senior members of the MIND Group, while all commentaries were written by junior group members. All papers and commentaries have undergone a rigorous process of anonymous peer review, during which the junior members of the MIND Group acted as reviewers. The final versions of all the target articles, commentaries and replies have undergone additional editorial review. Besides offering a cross-section of ongoing, cutting-edge research in philosophy and cognitive science, this collection is also intended to be a free electronic resource for teaching. It therefore also contains a selection of online supporting materials, pointers to video and audio files and to additional free material supplied by the 92 authors represented in this volume. We will add more multimedia material, a searchable literature database, and tools to work with the online version in the future. All contributions to this collection are strictly open access. They can be downloaded, printed, and reproduced by anyone.

Date

27. 1.2015 11:48:22

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Abstract

Semantic Web knowledge representation standards, and in particular RDF and OWL, often come endowed with a formal semantics which is considered to be of fundamental importance for the field. Reasoning, i.e., the drawing of logical inferences from knowledge expressed in such standards, is traditionally based on logical deductive methods and algorithms which can be proven to be sound and complete and terminating, i.e. correct in a very strong sense. For various reasons, though, in particular the scalability issues arising from the ever increasing amounts of Semantic Web data available and the inability of deductive algorithms to deal with noise in the data, it has been argued that alternative means of reasoning should be investigated which bear high promise for high scalability and better robustness. From this perspective, deductive algorithms can be considered the gold standard regarding correctness against which alternative methods need to be tested. In this paper, we show that it is possible to train a Deep Learning system on RDF knowledge graphs, such that it is able to perform reasoning over new RDF knowledge graphs, with high precision and recall compared to the deductive gold standard.

Date

16.11.2018 14:22:01

Type

a

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Abstract

You were going to get one-click access to the full text of nearly every book that's ever been published. Books still in print you'd have to pay for, but everything else-a collection slated to grow larger than the holdings at the Library of Congress, Harvard, the University of Michigan, at any of the great national libraries of Europe-would have been available for free at terminals that were going to be placed in every local library that wanted one. At the terminal you were going to be able to search tens of millions of books and read every page of any book you found. You'd be able to highlight passages and make annotations and share them; for the first time, you'd be able to pinpoint an idea somewhere inside the vastness of the printed record, and send somebody straight to it with a link. Books would become as instantly available, searchable, copy-pasteable-as alive in the digital world-as web pages. It was to be the realization of a long-held dream. "The universal library has been talked about for millennia," Richard Ovenden, the head of Oxford's Bodleian Libraries, has said. "It was possible to think in the Renaissance that you might be able to amass the whole of published knowledge in a single room or a single institution." In the spring of 2011, it seemed we'd amassed it in a terminal small enough to fit on a desk. "This is a watershed event and can serve as a catalyst for the reinvention of education, research, and intellectual life," one eager observer wrote at the time. On March 22 of that year, however, the legal agreement that would have unlocked a century's worth of books and peppered the country with access terminals to a universal library was rejected under Rule 23(e)(2) of the Federal Rules of Civil Procedure by the U.S. District Court for the Southern District of New York. When the library at Alexandria burned it was said to be an "international catastrophe." When the most significant humanities project of our time was dismantled in court, the scholars, archivists, and librarians who'd had a hand in its undoing breathed a sigh of relief, for they believed, at the time, that they had narrowly averted disaster.

Type

a

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Abstract

A dentograph is a visualization of a library's collection built on the idea that a classification scheme is a mathematical function mapping one set of things (books or the universe of knowledge) onto another (a set of numbers and letters). Dentographs can visualize aspects of just one collection or can be used to compare two or more collections. This article describes how to build them, with examples and code using Ruby and R, and discusses some problems and future directions.

Type

a

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Abstract

A publishing giant goes after the authors of its journals' papers

Type

a

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Abstract

In a new study, computer scientists found that artificial intelligence systems fail a vision test a child could accomplish with ease. "It's a clever and important study that reminds us that 'deep learning' isn't really that deep," said Gary Marcus , a neuroscientist at New York University who was not affiliated with the work. The result takes place in the field of computer vision, where artificial intelligence systems attempt to detect and categorize objects. They might try to find all the pedestrians in a street scene, or just distinguish a bird from a bicycle (which is a notoriously difficult task). The stakes are high: As computers take over critical tasks like automated surveillance and autonomous driving, we'll want their visual processing to be at least as good as the human eyes they're replacing. It won't be easy. The new work accentuates the sophistication of human vision - and the challenge of building systems that mimic it. In the study, the researchers presented a computer vision system with a living room scene. The system processed it well. It correctly identified a chair, a person, books on a shelf. Then the researchers introduced an anomalous object into the scene - an image of elephant. The elephant's mere presence caused the system to forget itself: Suddenly it started calling a chair a couch and the elephant a chair, while turning completely blind to other objects it had previously seen. Researchers are still trying to understand exactly why computer vision systems get tripped up so easily, but they have a good guess. It has to do with an ability humans have that AI lacks: the ability to understand when a scene is confusing and thus go back for a second glance.

Type

a

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Abstract

OpenRefine is described as a tool for working with 'messy' data - but what does this mean? It is probably easiest to describe the kinds of data OpenRefine is good at working with and the sorts of problems it can help you solve. OpenRefine is most useful where you have data in a simple tabular format but with internal inconsistencies either in data formats, or where data appears, or in terminology used. It can help you: Get an overview of a data set Resolve inconsistencies in a data set Help you split data up into more granular parts Match local data up to other data sets Enhance a data set with data from other sources Some common scenarios might be: 1. Where you want to know how many times a particular value appears in a column in your data. 2. Where you want to know how values are distributed across your whole data set. 3. Where you have a list of dates which are formatted in different ways, and want to change all the dates in the list to a single common date format.

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Abstract

In this paper, we describe in detail the Information Content Evaluation Map (ICE-Map Visualization, formerly referred to as IC Difference Analysis). The ICE-Map Visualization is a visual data mining approach for all kinds of concept hierarchies that uses statistics about the concept usage to help a user in the evaluation and maintenance of the hierarchy. It consists of a statistical framework that employs the the notion of information content from information theory, as well as a visualization of the hierarchy and the result of the statistical analysis by means of a treemap.

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Abstract

We present a novel unsupervised approach to detecting the compositionality of multi-word expressions. We compute the compositionality of a phrase through substituting the constituent words with their "neighbours" in a semantic vector space and averaging over the distance between the original phrase and the substituted neighbour phrases. Several methods of obtaining neighbours are presented. The results are compared to existing supervised results and achieve state-of-the-art performance on a verb-object dataset of human compositionality ratings.

Type

a