In an effort to increase beef demand, the beef industry has expanded beyond commodity beef merchandizing into value-added cuts. As these beef cuts are developed it is critical that the industry be able to characterize the flavor attributes of these products. A trained sensory panel is typically utilized to determine flavor characteristics of food products including beef. Prior to product evaluation, a product lexicon or dictionary of terms is developed in order to anchor and orient panelists to the various samples. Once the lexicon is developed, it can be used by a descriptive panel to evaluate samples. Currently, the beef industry does not have a full beef flavor lexicon with defined references; therefore a comprehensive sensory lexicon for describing the aroma and flavor of beef was developed by a 6-member panel at Kansas State University with extensive experience in lexicon development and descriptive analysis. Three descriptive panels utilized the beef flavor lexicon developed in Phase I by Kansas State University to evaluate the effect of USDA Quality Grade and cut on beef flavor and to validate the beef flavor lexicon to determine if it is ready for use by scientists. iv Results indicated that Choice steaks and roasts were higher in fat-like, and overall sweet flavor. Eye of round roasts were lowest in aroma and flavor attributes and bottom round roasts were highest in liver-like flavor. Flat iron steaks were highest in fat-like flavor compared to other cuts and top loin steaks tended to have the lowest intensity in flavor attributes compared to the steak cuts. The three sensory panels rated steaks and roasts similarly for aroma and flavor attributes and were generally less than 2- to 1-point different in rating intensities. The beef flavor lexicon was easily applied across the three institutions and should be ready to be used as a viable research and product development tool.

<p>In this masters’ thesis report we present a graph theoretical method used for automatic bilingual lexicon acquisition with parallel texts. We analyze the concept of graph similarity and give an interpretation, of the parallel texts, connected to the vector space model. We represent the parallel texts by a directed, tripartite graph and from here use the corresponding adjacency matrix, A, to compute the similarity of the graph. By solving the eigenvalue problem ρS = ASAT + ATSA we obtain the self-similarity matrix S and the Perron root ρ. A rank k approximation of the self-similarity matrix is computed by implementations of the singular value decomposition and the non-negative matrix factorization algorithm GD-CLS. We construct an algorithm in order to extract the bilingual lexicon from the self-similarity matrix and apply a statistical model to estimate the precision, the correctness, of the translations in the bilingual lexicon. The best result is achieved with an application of the vector space model with a precision of about 80 %. This is a good result and can be compared with the precision of about 60 % found in the literature.</p>

This paper presents and evaluates an algorithm to translate a dependency treebank into a Combinatory Categorial Grammar (CCG) lexicon. The dependency relations between a head and a child in a dependency tree are exploited to determine how CCG categories should be derived by making a functional distinction between adjunct and argument relations. Derivations for an English (CoNLL08 shared task treebank) and for an Italian (Turin University Treebank) dependency treebank are performed, each requiring a number of preprocessing steps. In order to determine the adequacy of the lexicons, dubbed DepEngCCG and DepItCCG, they are compared via two methods to preexisting CCG lexicons derived from similar or equivalent sources (CCGbank and TutCCG). First, a number of metrics are used to compare the state of the lexicon, including category complexity and category growth. Second, to measures the potential applicability of the lexicons in NLP tasks, the derived English CCG lexicon and CCGbank are compared in a sentiment analysis task. While the numeric measurements show promising results for the quality of the lexicons, the sentiment analysis task fails to generate a usable comparison. / text

This thesis addresses the borrowing and adaptation of the English discourse marker (DM) anyway into the speech of the Czech-speaking diaspora in Texas, known widely as Texas Czechs (TC). The primary goal of the thesis is to assess which subtypes of 'anyway', according to the schema of Ferrara (1997), are borrowed into TC, and to what extent. Chapter one addresses the sociolinguistic history of the TC community. The historical origins of the people and cultural background are provided. Late in the chapter, I provide a discussion of previous scholarship in the field of TC linguistics over the last half-century. Chapter two addresses the theories of borrowing and code-switching in language. The two are disambiguated, and a basic set of conditions which define the two are proposed. From this, I address Serra's (1998) theory of a mixed-code system, which relies on the knowledge of two separate codes for understanding, but also utilizes borrowings. The works of Fuller (2001) and Weilbacher (2007) in Pennsylvania and Texas German communities are addressed, as is Johnson's (1995) work on Tejano. The chapter concludes with a brief description of DMs. Chapter three describes the subtypes and features of 'anyway' in English according to Ferrara's (1997) schema, as well as surveys a number of possible counterparts for 'anyway' in standard European Czech. Chapter four analyzes borrowed 'anyway' in TC speech as a Ferraran subtype. I disambiguate the uses of various types of anyway, proposing that only anyway, Ferrara's only true DM, is borrowed in TC. I demonstrate that possible functions of native TC DMs similar to 'anyway' function inherently differently than those of Ferrara. I show that 'anyway' is borrowed into TC to fulfill a pragmatic gap in the form of 'anyway', whereas the two adverbial subtypes are not borrowed. In older data, these two were borrowed, but no examples exist in modern speech. I propose that this is indicative of the TC's existence as a mixed-code system, in that knowledge of both English and TC are required to properly choose the appropriate DM and to understand borrowed DMs from the other code. / text

Im Spannungsfeld zwischen der gültigen Repräsentation des aktuellen Wissensstandes und der allgemeinen Verständlichkeit für den nichtakademischen Leser stellt die enzyklopädische Literatur des 18. Jahrhunderts eine Praxis der Wissenserstellung und Wissensvermittlung dar, die an ihren Formen selbst studiert werden muss. Nach einer kurzen Erläuterung des Ansatzes (1.) werden nachfolgend diese Wissensformen als gattungsgenerierend (2.) und, am Beispiel von Zedlers Universal-Lexicon (3.), als textgenerierend für das allgemeine Wissen beschrieben.

The role of the lexicon has been ignored or minimized in most work on computational stylistics. This research is an effort to fill that gap, demonstrating the key role that the lexicon plays in stylistic variation. In doing so, I bring together a number of diverse perspectives, including aesthetic, functional, and sociological aspects of style. The first major contribution of the thesis is the creation of aesthetic stylistic lexical resources from large mixed-register corpora, adapting statistical techniques from approaches to topic and sentiment analysis. A key novelty of the work is that I consider multiple correlated styles in a single model. Next, I consider a variety of tasks that are relevant to style, in particular tasks relevant to genre and demographic variables, showing that the use of lexical resources compares well to more traditional approaches, in some cases offering information that is simply not available to a system based on surface features. Finally, I focus in on a single stylistic task, Native Language Identification (NLI), offering a novel method for deriving lexical information from native language texts, and using a cross-corpus supervised approach to show definitively that lexical features are key to high performance on this task.

The role of the lexicon has been ignored or minimized in most work on computational stylistics. This research is an effort to fill that gap, demonstrating the key role that the lexicon plays in stylistic variation. In doing so, I bring together a number of diverse perspectives, including aesthetic, functional, and sociological aspects of style. The first major contribution of the thesis is the creation of aesthetic stylistic lexical resources from large mixed-register corpora, adapting statistical techniques from approaches to topic and sentiment analysis. A key novelty of the work is that I consider multiple correlated styles in a single model. Next, I consider a variety of tasks that are relevant to style, in particular tasks relevant to genre and demographic variables, showing that the use of lexical resources compares well to more traditional approaches, in some cases offering information that is simply not available to a system based on surface features. Finally, I focus in on a single stylistic task, Native Language Identification (NLI), offering a novel method for deriving lexical information from native language texts, and using a cross-corpus supervised approach to show definitively that lexical features are key to high performance on this task.

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Το παρόν πόνημα αποτελεί μια προσπάθεια καταγραφής του λεξικού του Φιλωτίτικου ιδιώματος της Νάξου. Επιπλέον είναι εμπλουτισμένο με εισαγωγή που περιγράφει τη διάλεκτο σε όλα τα επίπεδα ανάλυσης της γλώσσας (μορφολογία, σύνταξη, φωνολογία, λεξικό). / This assignment constitutes an attempt of recording the dialectical lexicon of Filoti, a village of the island of Naxos. In addition, it has an introduction that describes the dialect in all level of linguistics (morphology, syntax, phonology, lexicon).