Statistical semantics methods and applications /: methods and applications. (2020)

• Record Type: Book
• Further Information: Note: Sverker Sikström, Danilo Garcia, editor.
• Other Names: Sikström, Sverker; Garcia, Danilo
• Contents: Intro -- Preface -- Preface -- Acknowledgment -- Contents -- Contributors -- Part I: Methods -- Chapter 1: Introduction to Statistical Semantics -- References -- Chapter 2: Creating Semantic Representations -- Vector Space Model -- Feature Hashing -- Random Indexing -- Latent Semantic Analysis -- Non-negative Matrix Factorization -- Explicit Semantic Analysis -- Word Embeddings -- Deep Learning Representations -- Creating Explicit Semantic Representations -- Creating Semantic Representations with Non-linguistic Information -- Evaluating Semantic Representations -- Word Similarity/Relatedness Verbal Analogies -- Word Intrusion -- Sentiment Analysis -- Challenges: Polysemy, Homograph, Bias and Compounds -- What Does It Mean? -- References -- Chapter 3: Software for Creating and Analyzing Semantic Representations -- Introduction -- Natural Language Processing Toolkit, NLTK -- spaCy -- Pattern -- Polyglot -- MediaWiki Processing Software -- Scikit-Learn -- Word Embedding -- Word2vec -- GloVe -- FastText -- Other Word Embedding Software -- Other Embedding Software -- Gensim -- Deep Learning -- Keras -- Explicit Creation of Semantic Representations -- References Chapter 4: Semantic Similarity Scales: Using Semantic Similarity Scales to Measure Depression and Worry -- Semantic Analysis Methods -- Using the Semantic Representations to Measure Semantic Similarity -- Applying High Quality Semantic Representations to Experimental Data -- Adding Semantic Representations Together to Represent Several Words or a Text -- Understanding Semantic Similarity -- Semantic t-Tests Computed on Semantic Similarities -- Research Study -- Assessing Psychological Constructs Using Semantic Similarity Scales: Measuring, Describing and Differentiating Depression and ... The Semantic Measures Approach: Semantic Questions and Word Norms -- Measuring Constructs: Unipolar and Bipolar Semantic Similarity Scales -- Describing Constructs Using Plots -- Differentiating Between Constructs: Inter-Correlations and Covarying Variables in Plots -- Method -- Participants -- Measures and Material -- Procedure -- Statistical Analyses -- Results -- Semantic Responses Differ Significantly -- Measuring Psychological Constructs -- Bipolar Scales Yield Stronger Correlations to Rating Scales than Unipolar Scales -- Describing Psychological Constructs Semantic Similarity Scales Differentiate Better Between Depression and Worry than Rating Scales -- Discussion -- Unipolar and Bipolar Scales -- Limitations and Future Research -- Concluding Remarks -- Chapter Summary -- Step-by-Step Computational Guides -- References -- Chapter 5: Prediction and Semantic Trained Scales: Examining the Relationship Between Semantic Responses to Depression and Wor... -- Semantic Analysis Methods -- Using the Semantic Representations to Predict Numerical Values -- Using the Semantic Representations in Multiple Linear Regression
• Publisher Details: Cham : Springer
• Publication Date: 2020
• Extent: 1 online resource (266 p.)
• Subjects: 401/.43; 153; Semantics -- Statistical methods; Electronic books; Electronic books
• Languages: English
• ISBNs: 9783030372507; 3030372502
• Related ISBNs: 3030372499; 9783030372491
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.