We present two eye-tracking experiments that investigate lexical frequency and semantic context constraints in spoken-word recognition in German. In both experiments, the pivotal words were pairs of nouns overlapping at onset but varying in lexical frequency. In Experiment 1, German listeners showed an expected frequency bias towards high-frequency competitors (e.g., Blume, 'flower') when instr...

The current study investigates to what extent masked morphological priming is modulated by language-particular properties, specifically by its writing system. We present results from two masked priming experiments investigating the processing of complex Japanese words written in less common (moraic) scripts. In Experiment 1, participants performed lexical decisions on target verbs; these were p...

links the clauses “you need anything” and “I’m Jill” in a conditional construction, but semantically we may naturally perceive the propositions expressed by these clauses as conditionally unrelated; the name of the woman does not depend on whether the addressee needs anything or not. To humorously misapprehend such conditional sentences, as Martin does, is to pretend to see a conditional relati...

The aim of the present paper is to investigate the encoding and decoding of informativeness of verbs in German. Pairs of target verbs and nouns were either semantically unrelated (i.e. new) or related to each other in different ways. In a production study using read speech, these differences in semantic relatedness were found to be expressed in the prosodic realisation of the target words, nucl...

An attentional blink (AB) paradigm was used to directly compare semantic and repetition priming for reported words versus missed words. Three target words (T1, T2, T3) were embedded in a rapidly presented stream of non-word distractors for report at the end of each trial. Whereas T1 was not related to either T2 or T3, T2 and T3 could be unrelated words, semantically related words, or identical....

Content-based information retrieval (IR) involves low-level feature extraction and utilize similarity search methods applied either in the feature space or in derived higher-level semantic spaces. These methods assume that similarity is measured by accounting only the degree in which two entities are related, ignoring the hesitancy introduced by the degree in which they are unrelated. Aiming at...

The distributed data problem is characterized by the desire to bring together semantically related data from syntactically unrelated portions of a term. A strategic combinator called transient and a strategic constant called skip is introduced in the context of a higher-order strategic framework. The notion of traversal is lifted to the higher-order as well. The resulting framework allows the m...

This article addresses a multi-stage flowshop scheduling problem with equal number of unrelated parallel machines. The objective is to minimize the makespan for a given set of jobs in the system. This problem class is NP-hard in the strong sense, so a hybrid heuristic method for sequencing and then allocating operations of jobs to machines is developed. A number of test problems are randomly ge...