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Computer Processing of Oriental Languages. Language Technology for the Knowledge-based Economy: 22nd International Conference, ICCPOL 2009, Hong Kong, March 26-27, 2009. Proceedings

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Cognitive Linguistics has been widely used to deal with the ambiguity generated by words in combination. Although this domain offers many solutions to address this challenge, not all of them can be implemented in a computational environment. The Dynamic Construal of Meaning framework is argued to have this ability because it describes an intrinsic degree of association of meanings, which in turn, can be translated into computational programs. A limitation towards a computational approach, however, has been the lack of syntactic parameters. This research argues that this limitation could be overcome with the aid of the Generative Lexicon Theory (GLT). Specifically, this dissertation formulated possible means to marry the GLT and Cognitive Linguistics in a novel rapprochement between the two. This bond between opposing theories provided the means to design a computational template (the AXEL System) by realising syntax and semantics at software levels. An instance of the AXEL system was created using a Design Research approach. Planned iterations were involved in the development to improve artefact performance. Such iterations boosted performance-improving, which accounted for the degree of association of meanings in three-noun compounds. This dissertation delivered three major contributions on the brink of a so-called turning point in Computational Linguistics (CL). First, the AXEL system was used to disclose hidden lexical patterns on ambiguity. These patterns are difficult, if not impossible, to be identified without automatic techniques. This research claimed that these patterns can assist audiences of linguists to review lexical knowledge on a software-based viewpoint. Following linguistic awareness, the second result advocated for the adoption of improved resources by decreasing electronic space of Sense Enumerative Lexicons (SELs). The AXEL system deployed the generation of “at the moment of use” interpretations, optimising the way the space is needed for lexical storage. Finally, this research introduced a subsystem of metrics to characterise an ambiguous degree of association of three-noun compounds enabling ranking methods. Weighing methods delivered mechanisms of classification of meanings towards Word Sense Disambiguation (WSD). Overall these results attempted to tackle difficulties in understanding studies of Lexical Semantics via software tools.

MASTERS FACULTY OF HUMANITIES SCHOOL OF LITERATURE AND LANGUAGE STUDIES STUDENT NO: 0111542N / The study deals with term creation in translation comparing isiXhosa and isiZulu in relation to paraphrasing, borrowing, compounding, semantic transfer and derivation as five major processes used by translators in African Languages to compensate for terminology gap. The study is conducted within the Descriptive Translation Studies approach and it deals with how translator’s strategies are influenced by norms. The extracted source text terms in this study are from the English Constitution as the source text whilst the isiXhosa and isiZulu terms are extracted from the isiXhosa and isiZulu Constitutions respectively. The study has indicated that out of the five selected processes, paraphrasing is the most frequently chosen strategy in African Languages. With regard to borrowing, it has been shown that not all types of borrowing (as discussed by Cluver 1989) are possible in these languages and that every borrowed term has to be modified according to phonological, morphological and orthographical rules of these two languages. The study is concluded by arguing that term creation processes in translation are universal features of translated texts in African languages and they are effective translation strategies in languages of limited diffusion. In addition, translated texts are sources/ depositories of terminology and consequently they can play a role in language development activities.

The purpose of this study was to examine differences in math problem solving among students with learning disabilities (LD), low-achieving (LA) students, and average-achieving (AA) students. The primary interest was to analyze the problem representation processes students use to translate and integrate problem information as they solve math word problems. Problem representation processes were operationalized as (a) paraphrasing the problem and (b) visually representing the problem. Paraphrasing accuracy (i.e., paraphrasing relevant information, paraphrasing irrelevant linguistic information, and paraphrasing irrelevant numerical information), visual representation accuracy (i.e., visual representation of relevant information, visual representation of irrelevant linguistic information, and visual representation of irrelevant numerical information), and problem-solving accuracy were measured in eighth-grade students with LD (n = 25), LA students (n = 30), and AA students (n = 29) using a researcher-modified version of the Mathematical Processing Instrument (MPI). Results indicated that problem-solving accuracy was significantly and positively correlated to relevant information in both the paraphrasing and the visual representation phases and significantly negatively correlated to linguistic and numerical irrelevant information for the two constructs. When separated by ability, students with LD showed a different profile as compared to the LA and AA students with respect to the relationships among the problem-solving variables. Mean differences showed that students with LD differed significantly from LA students in that they paraphrased less relevant information and also visually represented less irrelevant numerical information. Paraphrasing accuracy and visual representation accuracy were each shown to account for a statistically significant amount of variance in problem-solving accuracy when entered in a hierarchical model. Finally, the relationship between visual representation of relevant information and problem-solving accuracy was shown to be dependent on ability after controlling for the problem-solving variables and ability. Implications for classroom instruction for students with and without LD are discussed.

Paraphrasing is taught to postsecondary students to help them avoid plagiarism in their academic essays, but it can be challenging for native speakers (L1) as well as nonnative speakers (L2) of English. To examine these challenges I analyzed 35 paraphrases written by 4 English-Canadian students and 5 Japanese international students at an English-medium community college in Ontario. I evaluated paraphrase quality through a modified replication of Keck’s (2006) analytic method, and I analyzed paraphrase appropriateness through a set of criteria I developed and verified with a second rater. I then analyzed 6 concurrent and post-task reports of 3 L1 and 3 L2 students, who used a variety of paraphrasing strategies. All participants wrote relatively inappropriate paraphrases which did not always correspond with perceived appropriateness. L1 students tended to copy directly from the original text excerpts more often than the L2 students did. Implications for teaching and further research are discussed.

Paraphrasing is taught to postsecondary students to help them avoid plagiarism in their academic essays, but it can be challenging for native speakers (L1) as well as nonnative speakers (L2) of English. To examine these challenges I analyzed 35 paraphrases written by 4 English-Canadian students and 5 Japanese international students at an English-medium community college in Ontario. I evaluated paraphrase quality through a modified replication of Keck’s (2006) analytic method, and I analyzed paraphrase appropriateness through a set of criteria I developed and verified with a second rater. I then analyzed 6 concurrent and post-task reports of 3 L1 and 3 L2 students, who used a variety of paraphrasing strategies. All participants wrote relatively inappropriate paraphrases which did not always correspond with perceived appropriateness. L1 students tended to copy directly from the original text excerpts more often than the L2 students did. Implications for teaching and further research are discussed.

In this dissertation, we introduce a graph-based model of instance-based, usage meaning that is cast as a problem of probabilistic inference. The main aim of this model is to provide a flexible platform that can be used to explore multiple hypotheses about usage meaning computation. Our model takes up and extends the proposals of Erk and Pado [2007] and McCarthy and Navigli [2009] by representing usage meaning as a probability distribution over potential paraphrases. We use undirected graphical models to infer this probability distribution for every content word in a given sentence. Graphical models represent complex probability distributions through a graph. In the graph, nodes stand for random variables, and edges stand for direct probabilistic interactions between them. The lack of edges between any two variables reflect independence assumptions. In our model, we represent each content word of the sentence through two adjacent nodes: the observed node represents the surface form of the word itself, and the hidden node represents its usage meaning. The distribution over values that we infer for the hidden node is a paraphrase distribution for the observed word. To encode the fact that lexical semantic information is exchanged between syntactic neighbors, the graph contains edges that mirror the dependency graph for the sentence. Further knowledge sources that influence the hidden nodes are represented through additional edges that, for example, connect to document topic. The integration of adjacent knowledge sources is accomplished in a standard way by multiplying factors and marginalizing over variables. Evaluating on a paraphrasing task, we find that our model outperforms the current state-of-the-art usage vector model [Thater et al., 2010] on all parts of speech except verbs, where the previous model wins by a small margin. But our main focus is not on the numbers but on the fact that our model is flexible enough to encode different hypotheses about usage meaning computation. In particular, we concentrate on five questions (with minor variants): - Nonlocal syntactic context: Existing usage vector models only use a word's direct syntactic neighbors for disambiguation or inferring some other meaning representation. Would it help to have contextual information instead "flow" along the entire dependency graph, each word's inferred meaning relying on the paraphrase distribution of its neighbors? - Influence of collocational information: In some cases, it is intuitively plausible to use the selectional preference of a neighboring word towards the target to determine its meaning in context. How does modeling selectional preferences into the model affect performance? - Non-syntactic bag-of-words context: To what extent can non-syntactic information in the form of bag-of-words context help in inferring meaning? - Effects of parametrization: We experiment with two transformations of MLE. One interpolates various MLEs and another transforms it by exponentiating pointwise mutual information. Which performs better? - Type of hidden nodes: Our model posits a tier of hidden nodes immediately adjacent the surface tier of observed words to capture dynamic usage meaning. We examine the model based on by varying the hidden nodes such that in one the nodes have actual words as values and in the other the nodes have nameless indexes as values. The former has the benefit of interpretability while the latter allows more standard parameter estimation. Portions of this dissertation are derived from joint work between the author and Katrin Erk [submitted]. / text

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第17991号 / 情博第513号 / 新制||情||91(附属図書館) / 80835 / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 黒橋 禎夫, 教授 石田 亨, 教授 河原 達也 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM