10,247 research outputs found

    Error tolerant retrieval of trees

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    Cataloged from PDF version of article.We present an efficient algorithm for retrieving from a database of trees, all trees that differ from a given query tree by a small number additional or missing leaves, or leaf label changes. It has natural language processing applications in searching for matches in example-based translation systems, and retrieval from lexical databases containing entries of complex feature structures. For large randomly generated synthetic tree databases (some having tens of thousands of trees), and on databases constructed from Wall Street Journal treebank, it can retrieve for trees with a small error, in a matter of tenths of a second to about a second

    Lossless fault-tolerant data structures with additive overhead

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    12th International Symposium, WADS 2011, New York, NY, USA, August 15-17, 2011. ProceedingsWe develop the first dynamic data structures that tolerate δ memory faults, lose no data, and incur only an O(δ ) additive overhead in overall space and time per operation. We obtain such data structures for arrays, linked lists, binary search trees, interval trees, predecessor search, and suffix trees. Like previous data structures, δ must be known in advance, but we show how to restore pristine state in linear time, in parallel with queries, making δ just a bound on the rate of memory faults. Our data structures require Θ(δ) words of safe memory during an operation, which may not be theoretically necessary but seems a practical assumption.Center for Massive Data Algorithmics (MADALGO

    Error-Correcting Data Structures

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    We study data structures in the presence of adversarial noise. We want to encode a given object in a succinct data structure that enables us to efficiently answer specific queries about the object, even if the data structure has been corrupted by a constant fraction of errors. This new model is the common generalization of (static) data structures and locally decodable error-correcting codes. The main issue is the tradeoff between the space used by the data structure and the time (number of probes) needed to answer a query about the encoded object. We prove a number of upper and lower bounds on various natural error-correcting data structure problems. In particular, we show that the optimal length of error-correcting data structures for the Membership problem (where we want to store subsets of size s from a universe of size n) is closely related to the optimal length of locally decodable codes for s-bit strings.Comment: 15 pages LaTeX; an abridged version will appear in the Proceedings of the STACS 2009 conferenc

    On palimpsests in neural memory: an information theory viewpoint

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    The finite capacity of neural memory and the reconsolidation phenomenon suggest it is important to be able to update stored information as in a palimpsest, where new information overwrites old information. Moreover, changing information in memory is metabolically costly. In this paper, we suggest that information-theoretic approaches may inform the fundamental limits in constructing such a memory system. In particular, we define malleable coding, that considers not only representation length but also ease of representation update, thereby encouraging some form of recycling to convert an old codeword into a new one. Malleability cost is the difficulty of synchronizing compressed versions, and malleable codes are of particular interest when representing information and modifying the representation are both expensive. We examine the tradeoff between compression efficiency and malleability cost, under a malleability metric defined with respect to a string edit distance. This introduces a metric topology to the compressed domain. We characterize the exact set of achievable rates and malleability as the solution of a subgraph isomorphism problem. This is all done within the optimization approach to biology framework.Accepted manuscrip

    Searching by approximate personal-name matching

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    We discuss the design, building and evaluation of a method to access theinformation of a person, using his name as a search key, even if it has deformations. We present a similarity function, the DEA function, based on the probabilities of the edit operations accordingly to the involved letters and their position, and using a variable threshold. The efficacy of DEA is quantitatively evaluated, without human relevance judgments, very superior to the efficacy of known methods. A very efficient approximate search technique for the DEA function is also presented based on a compacted trie-tree structure.Postprint (published version

    World-view perspectives

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    The foundation of a tolerant society is an ability to foster and respond to the diversity of perspective among its people. Cognitive psychologists have described how perspective influences information processing, while our innate ability to adopt perspective has been established by neuropsychology. Literature, through the use of point-of-view, together with results from researchers adopting socio-cultural paradigms suggests perspective is also a social construct. An ecologically-based framework is described that provides cohesion to the temporal, spatial, universal and other types of world-view perspective associated, predominantly, with indigenous cultures. Culturally responsible types of creative and critical thinking are evoked when world-view perspective is engaged while reading text and reading the world. World-view perspective provides us with a means of critiquing the construction of knowledge through the de-construction of dominant discourses, re-valuing of indigenous world-views and reducing the relational distance between indigenous and non-indigenous peoples

    SHREC'16: partial matching of deformable shapes

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    Matching deformable 3D shapes under partiality transformations is a challenging problem that has received limited focus in the computer vision and graphics communities. With this benchmark, we explore and thoroughly investigate the robustness of existing matching methods in this challenging task. Participants are asked to provide a point-to-point correspondence (either sparse or dense) between deformable shapes undergoing different kinds of partiality transformations, resulting in a total of 400 matching problems to be solved for each method - making this benchmark the biggest and most challenging of its kind. Five matching algorithms were evaluated in the contest; this paper presents the details of the dataset, the adopted evaluation measures, and shows thorough comparisons among all competing methods
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