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In the last years, much effort went into the design of robust anaphor resolution algorithms. Many algorithms are based on antecedent filtering and preference strategies that are manually designed. Along a different line of research, corpus-based approaches have been investigated that employ machine-learning techniques for deriving strategies automatically. Since the knowledge-engineering effort for designing and optimizing the strategies is reduced, the latter approaches are considered particularly attractive. Since, however, the hand-coding of robust antecedent filtering strategies such as syntactic disjoint reference and agreement in person, number, and gender constitutes a once-for-all effort, the question arises whether at all they should be derived automatically. In this paper, it is investigated what might be gained by combining the best of two worlds: designing the universally valid antecedent filtering strategies manually, in a once-for-all fashion, and deriving the (potentially genre-specific) antecedent selection strategies automatically by applying machine-learning techniques. An anaphor resolution system ROSANA-ML, which follows this paradigm, is designed and implemented. Through a series of formal evaluations, it is shown that, while exhibiting additional advantages, ROSANAML reaches a performance level that compares with the performance of its manually designed ancestor ROSANA.
Syntactic coindexing restrictions are by now known to be of central importance to practical anaphor resolution approaches. Since, in particular due to structural ambiguity, the assumption of the availability of a unique syntactic reading proves to be unrealistic, robust anaphor resolution relies on techniques to overcome this deficiency. In this paper, two approaches are presented which generalize the verification of coindexing constraints to de cient descriptions. At first, a partly heuristic method is described, which has been implemented. Secondly, a provable complete method is specified. It provides the means to exploit the results of anaphor resolution for a further structural disambiguation. By rendering possible a parallel processing model, this method exhibits, in a general sense, a higher degree of robustness. As a practically optimal solution, a combination of the two approaches is suggested.
An anaphor resolution algorithm is presented which relies on a combination of strategies for narrowing down and selecting from antecedent sets for re exive pronouns, nonre exive pronouns, and common nouns. The work focuses on syntactic restrictions which are derived from Chomsky's Binding Theory. It is discussed how these constraints can be incorporated adequately in an anaphor resolution algorithm. Moreover, by showing that pragmatic inferences may be necessary, the limits of syntactic restrictions are elucidated.
Coreference-Based Summarization and Question Answering: a Case for High Precision Anaphor Resolution
(2003)
Approaches to Text Summarization and Question Answering are known to benefit from the availability of coreference information. Based on an analysis of its contributions, a more detailed look at coreference processing for these applications will be proposed: it should be considered as a task of anaphor resolution rather than coreference resolution. It will be further argued that high precision approaches to anaphor resolution optimally match the specific requirements. Three such approaches will be described and empirically evaluated, and the implications for Text Summarization and Question Answering will be discussed.
Eine spieltheoretische Analyse von Zulieferer-Abnehmer-Beziehungen auf Basis des JELS-Modells
(2001)
Elektronische Informationsressourcen, wie beispielsweise elektronische Zeitschriften und Datenbanken, gewannen in den letzten Jahren zunehmend an Bedeutung im Feld der akademischen Literaturversorgung. Mit diesem Trend einhergehend konnten Veränderungen der Bezugspraxis bei Bibliotheken einerseits und neue Preis- und Geschäftsmodelle bei Verlagen andererseits beobachtet werden. Neben der bequemeren Nutzbarkeit für die Leser bietet das neue Medium auch neue Formen des Kostencontrollings und der Optimierung für die Abnehmer. Dieser Workshop soll sich mit der Frage der Kostenrechnung und -verteilung für Konsortien für elektronische Informationsressourcen insbesondere eJournals beschäftigen. Dabei werden die neuen Möglichkeiten der Nutzungsmessung besonders berücksichtigt. Neben den theoretischen Ansätzen werden auch konkrete Beispielrechnungen durchgeführt und die Praktikabilität für die Umsetzung in der Praxis im besonderen Maße diskutiert.
Given x small epsilon, Greek Rn an integer relation for x is a non-trivial vector m small epsilon, Greek Zn with inner product <m,x> = 0. In this paper we prove the following: Unless every NP language is recognizable in deterministic quasi-polynomial time, i.e., in time O(npoly(log n)), the ℓinfinity-shortest integer relation for a given vector x small epsilon, Greek Qn cannot be approximated in polynomial time within a factor of 2log0.5 − small gamma, Greekn, where small gamma, Greek is an arbitrarily small positive constant. This result is quasi-complementary to positive results derived from lattice basis reduction. A variant of the well-known L3-algorithm approximates for a vector x small epsilon, Greek Qn the ℓ2-shortest integer relation within a factor of 2n/2 in polynomial time. Our proof relies on recent advances in the theory of probabilistically checkable proofs, in particular on a reduction from 2-prover 1-round interactive proof-systems. The same inapproximability result is valid for finding the ℓinfinity-shortest integer solution for a homogeneous linear system of equations over Q.
Gewalt in der Schule
(2004)