This study uses a moving windows self-paced reading task to assess both text comprehension and processing time of authentic texts and these same texts simplified to beginning and intermediate levels. Forty-eight second language learners each read 9 texts (3 different authentic, beginning, and intermediate level texts). Repeated measures ANOVAs reported linear effects of text type on reading tim...

Given a text, grammar-based compression is to construct a grammar that generates the text. There are many kinds of text compression techniques of this type. Each compression scheme is categorized as being either off-line or on-line, according to how a text is processed. One representative tactics for off-line compression is to substitute the longest repeated factors of a text with a production ...

We consider grammar-based text compression with longest first substitution (LFS), where non-overlapping occurrences of a longest repeating factor of the input text are replaced by a new non-terminal symbol. We present the first linear-time algorithm for LFS. Our algorithm employs a new data structure called sparse lazy suffix trees. We also deal with a more sophisticated version of LFS, called ...

We describe a modification of the Petri Net Linear Form notation to support the rendering of Unified Modeling Language (UML) Activity Diagrams as human-readable text. This new notation, called the Activity Diagram Linear Form, allows UML Activity Diagrams to be expressed in an alternate form with the superior accessibility, compatibility, and simplicity of use of a plain text representation. Fo...

Morrison’s Song of Solomon could be viewed as a paragon of trauma fiction. Since no narrative of trauma can be told in a linear way, Morrison tries to depict the overwhelming power of trauma through a non-linear narrative, episodic delivery, and flashbacks. Accordingly, the readers are compelled to concoct the disjointed and fragmented memories in order to solve the riddle of the text, in which...

Given a text and a pattern, the problem of pattern matching consists of determining all the positions of the text where the pattern occurs. When the text and the pattern are matrices, the matching is termed bidimensional. There are variations of this problem where we allow the matching using a somehow modified pattern. In this paper we assume that the pattern can be scaled. We propose a new par...

We observe that (1) it is difficult to combine transliteration and meaning translation when transforming named entities (NE); and (2) there are different translation variations in NE translation, due to different semantic information. From this basis, we propose a novel semantic-specific NE translation model, which automatically incorporates the global context from corpus in order to capture su...

We investigate the empirical behavior of ngram discounts within and across domains. When a language model is trained and evaluated on two corpora from exactly the same domain, discounts are roughly constant, matching the assumptions of modified Kneser-Ney LMs. However, when training and test corpora diverge, the empirical discount grows essentially as a linear function of the n-gram count. We a...

We propose a new indexing structure for parameterized strings, called parameterized position heap. Parameterized position heap is applicable for parameterized pattern matching problem, where the pattern matches a substring of the text if there exists a bijective mapping from the symbols of the pattern to the symbols of the substring. We propose an online construction algorithm of parameterized ...