This study presents an evaluation of WordNet-based semantic similarity and relatedness measures in tasks focused on concept similarity. Assuming similarity as distinct from relatedness, the goal is to fill a gap within the current body of work in the evaluation of similarity and relatedness measures. Past studies have either focused entirely on relatedness or only evaluated judgments over words...

This article focuses on dissociations between explicit and implicit expressions of memory during posthypnotic amnesia (PHA). Despite evidence of such dissociations, experimental design in this area has not always been consistent with contemporary memory research. Within a paradigm that aimed for conceptual and methodological clarity, we presented 40 high and 38 low hypnotizable individuals with...

Recently, neural network models for natural language processing tasks have been increasingly focused on for their ability to alleviate the burden of manual feature engineering. In this paper, we propose a novel neural network model for Chinese word segmentation called Max-Margin Tensor Neural Network (MMTNN). By exploiting tag embeddings and tensorbased transformation, MMTNN has the ability to ...

While previous research on readability has typically focused on document-level measures, recent work in areas such as natural language generation has pointed out the need of sentence-level readability measures. Much of psycholinguistics has focused for many years on processing measures that provide difficulty estimates on a word-by-word basis. However, these psycholinguistic measures have not y...

Background: Finding the right word is a necessity in communication, and its evaluation has always been a challenging clinical issue, suggesting the need for valid and reliable measurements. The Homophone Meaning Generation Test (HMGT) can measure the ability to switch between verbal concepts, which is required in word retrieval. The purpose of this study was to adapt and validate the Persian ve...

Pinyin-to-character conversion is an important task for Chinese natural language processing tasks. Previous work mainly focused on n-gram language models and machine learning approaches, or with additional hand-crafted or automatic rule-based post-processing. There are two problems unable to solve for word n-gram language model: out-of-vocabulary word recognition and long-distance grammatical c...

It is the second time that the Chinese Information Processing group of NLPR participates in TREC. In the past, we have investigated the use of two key technologies: Window-based weighting method and Semantic Tree Model for query expansion, with success, to tasks in novelty and robust tracks. We focused on the Robust Retrieval Track at this year’s conference. Based on the previous IR architectur...

In this paper, a new high precision focused word sense disambiguation (WSD) approach is proposed, which not only attempts to identify the proper sense for a word but also provides the probabilistic evaluation for the identification confidence at the same time. A novel Instance Knowledge Network (IKN) is built to generate and maintain semantic knowledge at the word, type synonym set and instance...

Much interest has recently been directed toward the knowledge of collocations in the field of second language learning since they have been asserted to improve fluency. The current study was intended to examine the effect of verbal and visuospatial working memory spans on the processing of collocations using a Self-Pace Reading Task (SPRT) and relevant working memory tasks. To this end, partici...