Estimating Quantitative Magnitudes Using Semantic Similarity
نویسندگان
چکیده
We present an AI called Visuo that guesses quantitative visuospatial magnitudes (e.g., heights, lengths) given adjective-noun pairs as input (e.g., “big hat”). It uses a database of tagged images as memory and infers unexperienced magnitudes by analogy with semanticallyrelated concepts in memory. We show that transferring width-height ratios from a semantically-related concept yields significantly lower error rates than using dissimilar concepts when predicting the width-height ratios of novel inputs.
منابع مشابه
A procedure for Web Service Selection Using WS-Policy Semantic Matching
In general, Policy-based approaches play an important role in the management of web services, for instance, in the choice of semantic web service and quality of services (QoS) in particular. The present research work illustrates a procedure for the web service selection among functionality similar web services based on WS-Policy semantic matching. In this study, the procedure of WS-Policy publi...
متن کاملDeepPurple: Estimating Sentence Semantic Similarity using N-gram Regression Models and Web Snippets
We estimate the semantic similarity between two sentences using regression models with features: 1) n-gram hit rates (lexical matches) between sentences, 2) lexical semantic similarity between non-matching words, and 3) sentence length. Lexical semantic similarity is computed via co-occurrence counts on a corpus harvested from the web using a modified mutual information metric. State-of-the-art...
متن کاملPresentation of an efficient automatic short answer grading model based on combination of pseudo relevance feedback and semantic relatedness measures
Automatic short answer grading (ASAG) is the automated process of assessing answers based on natural language using computation methods and machine learning algorithms. Development of large-scale smart education systems on one hand and the importance of assessment as a key factor in the learning process and its confronted challenges, on the other hand, have significantly increased the need for ...
متن کاملPresentation of an efficient automatic short answer grading model based on combination of pseudo relevance feedback and semantic relatedness measures
Automatic short answer grading (ASAG) is the automated process of assessing answers based on natural language using computation methods and machine learning algorithms. Development of large-scale smart education systems on one hand and the importance of assessment as a key factor in the learning process and its confronted challenges, on the other hand, have significantly increased the need for ...
متن کاملDeveloping a Semantic Similarity Judgment Test for Persian Action Verbs and Non-action Nouns in Patients With Brain Injury and Determining its Content Validity
Objective: Brain trauma evidences suggest that the two grammatical categories of noun and verb are processed in different regions of the brain due to differences in the complexity of grammatical and semantic information processing. Studies have shown that the verbs belonging to different semantic categories lead to neural activity in different areas of the brain, and action verb processing is r...
متن کامل