Glossary

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DBSCAN(also: Density-Based Spatial Clustering of Applications with Noise)

A density-based clustering algorithm introduced by Ester, Kriegel, Sander, and Xu (1996) that groups data points located in dense neighbourhoods and labels sparse points as noise. Unlike k-means, DBSCAN does not require the user to specify the number of clusters in advance and…

Data Descriptor(also: Training Data Descriptor)

An automated metric or feedback mechanism that characterizes the quality or properties of a dataset, particularly training images used in machine learning. In accessibility research, data descriptors provide non-visual feedback to blind users about the quality of photos they…

Data Mining(also: Knowledge Discovery, KDD, Knowledge Discovery in Databases)

Data mining is the computational process of discovering patterns, rules, and relationships in large datasets, drawing on techniques from statistics, machine learning, and database systems. Common tasks include classification, clustering, association-rule mining, anomaly…

Data Representativeness(also: Dataset Representativeness, Demographic Representativeness)

The degree to which a dataset reflects the diversity of the population it is intended to serve, particularly across demographic dimensions such as age, gender, race, ethnicity, disability, and socioeconomic status. In AI and machine learning, unrepresentative training data leads…

Dataset Bias(also: Training Data Bias, Data Representation Bias, Sampling Bias)

A systematic skew in the composition of training data used to build machine learning models, resulting in models that perform well for overrepresented groups but poorly for underrepresented ones. In accessibility contexts, dataset bias is a pervasive problem: activity…

Debiasing(also: Bias mitigation, Bias correction)

Debiasing refers to techniques and processes applied to AI systems—particularly machine learning models and large language models—to detect, reduce, or eliminate unfair biases that cause the system to produce outputs that discriminate against or misrepresent specific demographic…

Decision Tree(also: Classification Tree, Regression Tree, C4.5)

A decision tree is a supervised machine-learning model that represents a classification or regression decision as a tree of yes/no tests on input features, with predictions at the leaves. Well-known algorithms include ID3, C4.5, CART, and Random Forests. Decision trees are…

Diffusion Model(also: Diffusion-based Generator, Denoising Diffusion Model)

A diffusion model is a class of generative AI that learns to produce images or videos by iteratively denoising a random noise input, reversing a forward process that gradually adds noise to training data. In accessibility work, diffusion models are used to synthesize sign…

Document Expansion(also: Query Prediction, Document Enrichment)

An information retrieval technique that enhances a document by augmenting it with additional terms or predicted queries that users might use to search for that content. Methods like DocTTTTTQuery use sequence-to-sequence machine learning models to generate likely search queries…

Document Layout Analysis(also: DLA, page layout analysis)

A computer-vision task that identifies and classifies the visual regions of a document page—headings, paragraphs, tables, figures, captions, lists, headers, and footers—typically using object-detection models trained on datasets such as DocLayNet, PubLayNet, or DocBank. Document…

Domain Adaptation(also: Cross-Domain Transfer, UDA, Unsupervised Domain Adaptation)

A machine learning technique that enables models trained on data from one domain (such as web interfaces) to perform well on a different but related domain (such as mobile app interfaces). Domain adaptation is valuable for accessibility because it allows models trained on…

Dynamic Bayesian Network(also: DBN, Temporal Bayesian Network)

A probabilistic graphical model that represents sequences of variables over time, extending standard Bayesian networks to handle temporal relationships. In accessibility and affective computing contexts, Dynamic Bayesian Networks are used to model how facial expressions, head…

Dynamic Programming(also: DP, DP Matching)

A mathematical optimization technique used in pattern recognition that breaks complex problems into simpler overlapping subproblems. In accessibility technology, dynamic programming matching (DP matching) is commonly used in sign language recognition and speech recognition…

Dynamic Time Warping(also: DTW)

An algorithm for measuring similarity between two temporal sequences that may vary in speed or timing. Dynamic time warping aligns sequences by warping the time axis to find the optimal match, making it robust to variations in how quickly gestures are performed. DTW is commonly…

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