Schematic information influences memory and generalisation behaviour for schema-relevant and -irrelevant information

Schemas modulate memory performance for schema-congruent and -incongruent information. However, it is typically assumed they do not influence behaviour for information irrelevant to themselves. We assessed memory and generalisation behaviour for information related to an underlying pattern, where a schema could be extracted (schema-relevant), and information that was unrelated and therefore irrelevant to the extracted schema (schema-irrelevant). Using precision measures of long-term memory, where participants learnt associations between words and locations around a circle, we assessed memory and generalisation for schema-relevant and -irrelevant information. Words belonged to two semantic categories: human-made and natural. For one category, word-locations were clustered around one point on the circle (clustered condition), while the other category had word-locations randomly distributed (non-clustered condition). The presence of an underlying pattern in the clustered condition allows for the extraction of a schema that can support both memory and generalisation. At test, participants were presented with old (memory) and new (generalisation) words, requiring them to identify a remembered location or make a best guess. The presence of the clustered pattern modulated memory and generalisation. In the clustered condition, participants placed old and new words in locations consistent with the underlying pattern. In contrast, for the non-clustered condition, participants were less likely to place old and new non-clustered words in locations consistent with the clustered condition. We therefore provide evidence that the presence of schematic information modulates memory and generalisation for schema-relevant and -irrelevant information. Our results highlight the need to carefully construct appropriate schema-irrelevant control conditions such that behaviour in these conditions is not modulated by the presence of a schema. Theoretically, models of schema processing need to account for how the presence of schematic information can have consequences for information that is technically irrelevant to itself.

Dataless Short Text Classification Based on Biterm Topic Model and Word Embeddings

Dataless text classification has attracted increasing attentions recently. It only needs very few seed words of each category to classify documents, which is much cheaper than supervised text classification that requires massive labeling efforts. However, most of existing models pay attention to long texts, but get unsatisfactory performance on short texts, which have become increasingly popular on the Internet. In this paper, we at first propose a novel model named Seeded Biterm Topic Model (SeedBTM) extending BTM to solve the problem of dataless short text classification with seed words. It takes advantage of both word co-occurrence information in the topic model and category-word similarity from widely used word embeddings as the prior topic-in-set knowledge. Moreover, with the same approach, we also propose Seeded Twitter Biterm Topic Model (SeedTBTM), which extends Twitter-BTM and utilizes additional user information to achieve higher classification accuracy. Experimental results on five real short-text datasets show that our models outperform the state-of-the-art methods, and especially perform well when the categories are overlapping and interrelated.

Kategori Leksikal Idiom dalam Bahasa Lampung

This research aimed to describe lexical category (word class) and meaning of idiom in Lampung language. Descriptive qualitative was used in this research. The findings showed that idiom in Lampung language could be in form of complex word, word combination, and idiomatic expression. There were two idioms in complex word namely penghenguk and pedatong . Idiom in form of word combination could be a combination of noun+noun, noun+adjective, noun+verb, verb+adjective and verb+verb. The conclusion of the research based on verb semantic attitude that was used in form of words combination like state verb and action verb Keywords: Lexical, idiom, Lampung language.

A cognitive approach to SUFF1-SUFF2 combinations: A tribute to Carl Friedrich Gauss

This article discusses the further derivation of already derived words. With the help of a problem-solving strategy (Gauss-Jordan elimination) borrowed from mathematics, a solution to the suffix order puzzle is suggested. It is shown that there is a systematic relationship between a derived base (terminating in SUFF1) and the syntactic-category specification of the SUFF2 suffixes that attach to it. There is a clear tendency for a SUFF1 to select only one particular SUFF2 of a major syntactic category (word class), N, V and ADJ. If more than one SUFF2 with the same syntactic (word-class) specification exists, either one of the SUFF2 suffixes applies by default (i.e. most of the derivatives exhibit that suffix) or semantic rules differentiate between the different SUFF2 suffixes and allow the attachment of only one particular SUFF2 depending on what the speaker intends and due to blocking. Moreover, since derivation is prototypically word-class-changing, SUFF1 and SUFF2 usually have different word-class specifications. The syntactic specification of a suffix is cognitively defined in terms of semantic concepts. Data from English and Bulgarian illustrate the argument.

Are word meanings corresponding to different grammatical categories organised differently within lexical semantic memory?

We report on two experiments that examined lexical semantic memory. Experiment 1 included semantically related word-pairs (similarity of meaning) and unrelated word-pairs from three grammatical categories (nouns, verbs, adjectives). Experiment 2 included semantically related word-pairs (contrasting meaning) and unrelated word-pairs from the same three categories. Results of both experiments showed similar levels of semantic priming across same versus different grammatical category word-pairs (e.g., verb–verb pairs vs. verb–adjective pairs). Additional analyses of each experiment showed similar levels of priming within each of the three grammatical categories (i.e., noun–noun vs. verb–verb vs. adjective–adjective pairs). These findings suggest that there are no sharp architectural distinctions amongst words from different grammatical categories within lexical semantic memory.