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ediscovery

legal e-discovery with technology-assisted review

Relativity, Everlaw, DISCO

SystemTechniques · 9Primitives · 50 ediscovery Active learningmachine-learning · medium: Choosing which unlabeled examples to label next: uncertainty, margin, diversity and committee samplingNamed entity recognitionmachine-learning · medium: Find the character spans of entities in text and give each a type, by labelling every token and decoding a valid label sequence.›Near-duplicate detection with MinHa…machine-learning · medium: Estimate set Jaccard similarity from k min-hashes and find similar pairs with banded LSH buckets; the standard dedup for web crawls, training corpora and sequence collections.›Optical character recognition (text…machine-learning · medium: Find text lines in an image, read each crop with a CTC or attention model, then correct with a lexicon and score confidence for review routing.›Text classificationmachine-learning · medium: Assign one or more labels to a text; climb a ladder from regexes to linear models on n-grams, embeddings, fine-tuned encoders and LLM prompts, only as far as the data and budget demand.›Data maskingsecurity · medium: Hide sensitive field values from people and systems that don't need them, by masked copies or role-based masking at read time, while keeping joins and formats working.›Tamper-evident audit logsecurity · medium: An append-only log whose Merkle root, signed per batch, lets anyone verify an entry is present and history was never rewritten, with log-size proofs.›k-means clusteringmachine-learning · low: Partition points into k clusters by alternating nearest-centroid assignment and centroid averaging; k-means++ seeding makes it dependable.›Object storagecloud · low: S3-compatible blob storage at cents per GB-month with 11 nines durability; pick by egress price, request price and latency, not by storage price alone.›Deflatecompression · low: DEFLATE/gzip: LZ77 + Huffman, the format behind HTTP gzip, zip and PNGLanguage identificationmachine-learning · low: Score a text's character n-grams against per-language statistics, after a cheap script check, and return an ISO 639 code with a confidence or "und".›PDF text extractionmachine-learning · low: Rebuild words, lines, columns and reading order from the glyph positions a born-digital PDF stores, and route pages without usable text to OCR.›Image codecsmedia · low: JPEG (DCT, Huffman), PNG, HEIF/AVIF decoding and encoding fundamentalsUnicode text tokenization for searchsearch-sort · low: Turn multilingual text into index terms: segment words (UAX 29 style, CJK bigrams), normalize, case-fold and accent-fold, identically at index and query time.›Authorization models (RBAC, ABAC, R…security · low: How to decide who may do what to which object; roles for coarse rules, relationships for sharing, and checks on every object.›Cryptographic hashes (SHA-2, BLAKE3)security · low: Collision-resistant fingerprints of data; SHA-256 for interoperability, BLAKE3 for speed, HMAC/HKDF for keyed uses.›Wilson score intervalstatistics · low: Wilson lower bound for ranking by up/down votes and proportions with few samplesEmail threadingstorage · low: Threading messages by Message-ID/References (JWZ algorithm) and subject fallbackGapless sequence numbersstorage · low: Gap-free, monotonic numbering (invoices, journal entries) under concurrency and rollbacksMime parsingstorage · low: RFC 5322/2045 headers, multipart bodies and transfer encodingsCalibrationmachine-learning · low: Make predicted probabilities match observed frequencies: measure with ECE, fix post hoc with temperature, Platt or isotonic scaling on held-out data.›Embeddingsmachine-learning · low: A learned table mapping discrete ids to dense vectors: gather forward, sparse scatter-add backward, row-wise optimizers to keep huge tables cheap.›Byte-pair encoding (BPE) tokenizati…machine-learning · low: Learn a subword vocabulary by repeatedly merging the most frequent adjacent pair; byte-level BPE encodes any input losslessly with 32k-200k tokens.›+ 2 more techniques+ 34 more primitives

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