Browsing by Subject "Formal languages"

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    Handwritten mathematical formula recognition using a statistical approach
    (IEEE, 2011-04) Çelik, Mehmet; Yanıkoğlu, B.
    We present a probabilistic framework for a mathematical expression recognition system. The system is flexible in that its grammar can be extended easily, thanks to its graph grammar which eliminates the need for specifying rule precedence. It is also optimal in the sense that all possible interpretations of the expressions are expanded, without making early commitments or hard decisions. The current system is able to recognize shorter expressions well and in real time. In this paper, we give an overview of the whole system and describe in detail our context sensitive graph grammar and the parsing process.
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    Inducing translation templates with type constraints
    (Springer, 2005) Çiçekli, İlyas
    This paper presents a generalization technique that induces translation templates from a given set of translation examples by replacing differing parts in the examples with typed variables. Since the type of each variable is inferred during the learning process, each induced template is also associated with a set of type constraints. The type constraints that are associated with a translation template restrict the usage of the translation template in certain contexts in order to avoid some of the wrong translations. The types of variables are induced using type lattices designed for both the source and target languages. The proposed generalization technique has been implemented as a part of an example-based machine translation system.
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    Parsing Turkish using the lexical functional grammar formalism
    (Springer/Kluwer Academic Publishers, 1995) Güngördü, Z.; Oflazer, K.
    This paper describes our work on parsing Turkish using the lexical-functional grammar formalism [11]. This work represents the first effort for wide-coverage syntactic parsing of Turkish. Our implementation is based on Tomita's parser developed at Carnegie Mellon University Center for Machine Translation. The grammar covers a substantial subset of Turkish including structurally simple and complex sentences, and deals with a reasonable amount of word order freeness. The complex agglutinative morphology of Turkish lexical structures is handled using a separate two-level morphological analyzer, which has been incorporated into the syntactic parser. After a discussion of the key relevant issues regarding Turkish grammar, we discuss aspects of our system and present results from our implementation. Our initial results suggest that our system can parse about 82% of the sentences directly and almost all the remaining with very minor pre-editing. © 1995 Kluwer Academic Publishers.
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    Probabilistic mathematical formula recognition using a 2D context-free graph grammar
    (IEEE, 2011) Çelik, Mehmet; Yanikoglu, B.
    We present a probabilistic framework for the mathematical expression recognition problem. The developed system is flexible in that its grammar can be extended easily thanks to its graph grammar which eliminates the need for specifying rule precedence. It is also optimal in the sense that all possible interpretations of the expressions are expanded without making early commitments or hard decisions. In this paper, we give an overview of the whole system and describe in detail the graph grammar and the parsing process used in the system, along with some preliminary results on character, structure and expression recognition performances. © 2011 IEEE.
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    Querying web metadata: Native score management and text support in databases
    (Association for Computing Machinery, 2004) Özsoyoǧlu, G.; Altingövde, I. S.; Al-Hamdani, A.; Özel, S. A.; Ulusoy, Özgür; Özsoyoǧlu, Z. M.
    In this article, we discuss the issues involved in adding a native score management system to object-relational databases, to be used in querying Web metadata (that describes the semantic content of Web resources). The Web metadata model is based on topics (representing entities), relationships among topics (called metalinks), and importance scores (sideway values) of topics and metalinks. We extend database relations with scoring functions and importance scores. We add to SQL score-management clauses with well-defined semantics, and propose the sidewayvalue algebra (SVA), to evaluate the extended SQL queries. SQL extensions and the SVA algebra are illustrated through two Web resources, namely, the DBLP Bibliography and the SIGMOD Anthology. SQL extensions include clauses for propagating input tuple importance scores to output tuples during query processing, clauses that specify query stopping conditions, threshold predicates (a type of approximate similarity predicates for text comparisons), and user-defined-function-based predicates. The propagated importance scores are then used to rank and return a small number of output tuples. The query stopping conditions are propagated to SVA operators during query processing. We show that our SQL extensions are well-defined, meaning that, given a database and a query Q, under any query processing scheme, the output tuples of Q and their importance scores stay the same. To process the SQL extensions, we discuss two sideway value algebra operators, namely, sideway value algebra join and topic closure, give their implementation algorithms, and report their experimental evaluations.