Parsing with restricted quantification: an initial demonstration1

The primary goal of this paper is to illustrate how smaller deductive search spaces can be obtained by extending a logical language with restricted quantification and tailoring an inference system to this extension. The illustration examines the search spaces for a bottom-up parse of a sentence with a series of four strongly equivalent grammars. The grammars are stated in logical languages of increasing expressiveness, each restatement resulting in a more concise grammar and a smaller search space. A secondary goal is to point out an area where further research could yield results useful to the design of efficient parsers, particularly for grammatical formalisms that rely heavily on feature systems.     

Incremental generation of LR parsers

Implementation of a new compiler usually requires making frequent adjustments to grammar definitions. An incremental technique for updating the parser tables after a monor change to the grammer could potentially save much computational effort. More importantly, debugging a grammar is made easier if the grammar is re-checked for correctness after each small change to the grammar. The basic design philosophy of an incremental parser generator, and incremental algorithms for LR(0), SLR(1) and LALR(1) parser generation are discussed in this paper. Some of these algorithms have been incorporated into an implementation of an incremental LALR(1) parser generator.     

A new parallel algorithm for parsing arithmetic infix expressions

A new parallel algorithm for transforming an arithmetic infix expression into a par se tree is presented. The technique is based on a result due to Fischer (1980) which enables the construction of the parse tree, by appropriately scanning the vector of precedence values associated with the elements of the expression. The algorithm presented here is suitable for execution on a shared memory model of an SIMD machine with no read/write conflicts permitted. It uses O(n) processors and has a time complexity of O(log²n) where n is the expression length. Parallel algorithms for generating code for an SIMD machine are also presented.     

An Empirical Approach to Spanish Anaphora Resolution

This paper documents the development of an empirically-basedsystem implemented in Prolog that automatically resolves severalkinds of anaphora in Spanish texts. These are pronominalreferences, surface-count anaphora, one-anaphora and ellipticalzero-subject constructions (i.e., sentences that omit theirpronominal subject). The resolution is based onrepresentations resulting from either partial or full parsing. Thesystem developed can also work on the output of a POStagger or with different dictionaries, without changing thegrammar. This grammar represents the syntactic information of eachlanguage by means of the Slot Unification Grammar formalism. The different kinds of information used for anaphora resolution in full and partial parsing are shown, as wellas evaluation results. The system has been adapted toEnglish texts, obtaining encouraging results that prove that itcan be applied with only a very few refinements to other languagesas well as Spanish and English. In addition, the differencesbetween English and Spanish anaphora are noted.     

Incremental recursive descent parsing

The Recursive Descent method of parsing is well established in practice. An Incremental Parsing algorithm using the Recursive Descent method is presented. The algorithm is applicable to LL(1) grammars. The algorithm has been implemented for a subset of Pascal.     

Automatic parsing and indexing of news video

Automatic construction of content-based indices for video source material requires general semantic interpretation of both images and their accompanying sounds; but such a broadly-based semantic analysis is beyond the capabilities of the current technologies of machine vision and audio signal analysis. However, if one can assume a limited and well-demarcated body of domain knowledge for describing the content of a body of video, then it becomes easier to interpret a video source in terms of that domain knowledge. This paper presents our work on using domain knowledge to parse news video programs and to index them on the basis of their visual content. Models based on both the spatial structure of image frames and the temporal structure of the entire program have been developed for news videos, along with algorithms that apply these models by locating and identifying instances of their elements. Experimental results are also discussed in detail to evaluate both the models and the algorithms that use them. Finally, proposals for future work are summarized.     

一种电能质量多扰动分类中特征组合优化方法

针对电能质量扰动分类中冗余特征量造成分类器训练困难、分类准确率下降的问题,提出一种基于改进遗传算法的特征组合优化方法。该方法对信号进行小波变换,提取各层的改进小波能量熵作为原始特征,并构造一种基于欧氏距离的适应度函数,采用改进的自适应遗传算法对原始特征进行筛选和优化组合,形成用于电能质量扰动分类的最优特征组合。分别采用二分类-支持向量机法(Binary-SVM)、多标签径向基神经网络(ML-RBF)和多标签K近邻法(ML-KNN)对不同噪声情况下的电能质量单一扰动和混合扰动进行分类,仿真结果验证了所提特征组合优化方法能有效提高分类器的训练速度和分类准确率。     

Priming Prepositional-Phrase Attachment During Comprehension.

Strong evidence suggests that prior syntactic context affects language production (e.g., J. K. Bock, 1986). The authors report 4 experiments that used an expression-picture matching task to investigate whether it also affects ambiguity resolution in comprehension. All experiments examined the interpretation of prepositional phrases that were ambiguous between high and low attachment. After reading a prime expression with a high-attached interpretation, participants tended to interpret an ambiguous prepositional phrase in a target expression as highly attached if it contained the same verb as the prime (Experiment 1), but not if it contained a different verb (Experiment 2). They also tended to adopt the high-attached interpretation after producing a prime with the high-attached interpretation that included the same verb (Experiment 3). Finally, they were faster to adopt a high-attached interpretation after reading an expression containing the same verb that was disambiguated to the high-attached versus the low-attached interpretation (Experiment 4). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

INTERACTIVE SEMANTIC ANALYSIS OF TECHNICAL TEXTS

Sentence syntax is the basis for organizing semantic relations in TANKA, a project that aims to acquire knowledge from technical text. Other hallmarks include an absence of precoded domain-specific knowledge; significant use of public-domain generic linguistic information sources; involvement of the user as a judge and source of expertise; and learning from the meaning representations produced during processing. These elements shape the realization of the TANKA project: implementing a trainable text processing system to propose correct semantic interpretations to the user. A three-level model of sentence semantics, including a comprehensive Case system, provides the framework for TANKA's representations. Text is first processed by the DIPETT parser, which can handle a wide variety of unedited sentences. The semantic analysis module HAIKU then semi-automatically extracts semantic patterns from the parse trees and composes them into domain knowledge representations. HAIKU's dictionaries and main algorithm are described with the aid of examples and traces of user interaction. Encouraging experimental results are described and evaluated.