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Language Learning › Learn Japanese › Vocabulary ›

Vocabulary by Frequency

Learning high-frequency words first maximizes comprehension per hour of study. The top 500 words cover ~70% of casual speech; the top 2,000 cover ~90% of most general text. Top Verbs by Frequency Rank Japanese Reading Romaji English JLPT 1 する する suru to do N5 2 ある ある aru to exist/have (inanimate) N5 3 いる いる iru to exist/be (animate) N5 4 言う いう iu to say N5 5 行く...
japanese vocabulary frequency jlpt language-learning May 30, 2026
Language Learning › Learn Latin › Latin Vocabulary ›

DCC Latin Core Vocabulary

The DCC Latin Core Vocabulary (compiled by Christopher Francese at Dickinson College, 2012–13) is the gold standard frequency-based vocabulary list for Latin learners. About the DCC Core Property Details Total words ~1,000 headwords (lemmas) Compiled by Christopher Francese, Dickinson College Year 2012–13 Coverage 91% of Caesar's Gallic War ; 81% of Virgil's Aeneid Coverage (general) 70–80% of word forms in typical Latin text Available as Anki deck, physical book, web...
latin vocabulary dcc frequency anki May 30, 2026
Language Learning › Learn Latin › Latin Vocabulary › DCC Latin Core Vocabulary ›

DCC Core Vocabulary Band 1 (Words 1–200)

How to Use Band 1 The DCC (Dickinson College Commentaries) Core Latin Vocabulary is a list of the 1,000 most frequently occurring Latin words , compiled by Christopher Francese. Knowing Band 1 (the top 200) gives you coverage of the overwhelming majority of running Latin text — these words recur constantly in Caesar, Cicero, Virgil, and Livy. Study strategy: Learn all 200 words in Band 1 before moving to Band...
latin vocabulary dcc band1 frequency May 30, 2026
Language Learning › Learn Esperanto › Vocabulary ›

Frequency Lists

About Frequency Lists Frequency lists rank Esperanto roots by how often they appear in authentic text (books, articles, websites, spoken transcripts). Learning the most frequent roots first is the single most efficient vocabulary strategy. Key insight: In most languages, the top 300 words cover ~65% of text, and the top 1,000 cover ~85%. Esperanto's word-building system makes frequency lists even more powerful — learning a top-100 root often gives you...
esperanto vocabulary frequency anki May 30, 2026
Language Learning › Learn Latin › Latin Vocabulary › DCC Latin Core Vocabulary ›

DCC Core Vocabulary Band 2 (Words 201–500)

Band 2 covers words ranked 201–500 in the DCC Latin Core — the high-frequency vocabulary that unlocks fluent reading of Caesar, Cicero, Livy, and Virgil. Master these after Band 1 is solid. The 300 words here are grouped in sets of 50 for spaced-repetition chunking. Group 1 — Words 201–250: More Core Verbs # Latin Entry Form Part of Speech English 201 currō currō, currere, cucurrī, cursum verb (3rd conj.)...
latin vocabulary dcc band2 frequency May 30, 2026
Language Learning › Learn Esperanto ›

Vocabulary

Vocabulary Overview Esperanto vocabulary learning is highly efficient because: Roots are shared with European languages — most roots come from Latin, Romance, Germanic, and Slavic sources Word building multiplies roots — learning one root gives you 4+ words (noun/adj/adv/verb forms) plus derivations No vocabulary exceptions — words mean what their components suggest Frequency is concentrated — the top 500 roots cover ~80% of everyday text Sections Section Contents Frequency Lists...
esperanto vocabulary frequency thematic May 30, 2026
Language Learning › Learn Chinese (Mandarin) › Chinese Vocabulary ›

Chinese Vocabulary by Frequency

Frequency lists based on the SUBTLEX-CH corpus (Cai & Brysbaert 2010), derived from ~33 million words of Chinese subtitle text. Coverage Statistics List Words Text Coverage Top 100 words 100 ~65% of everyday text Top 500 words 500 ~75% of conversation Top 1,000 characters 1,000 ~90% of common written text Top 3,000 words 3,000 ~90% of standard modern text Top 10,000 words 10,000 ~99%+ of modern text Key insight :...
chinese vocabulary frequency corpus May 30, 2026
Language Learning › Learn Latin ›

Latin Vocabulary

How Latin Vocabulary Works Unlike HSK (which assigns vocabulary to levels), Latin vocabulary is organized primarily by corpus frequency — how often words appear across all classical texts. The key insight from research: the ~1,000 most frequent Latin words cover 70–80% of word forms in any typical Latin text. Specifically: DCC Core 1,000 words cover 91% of Caesar's Gallic War DCC Core 1,000 words cover 81% of Virgil's Aeneid This...
latin vocabulary dcc frequency roots May 30, 2026
Language Learning › Learn Latin › Latin Vocabulary ›

Latin Frequency Vocabulary — Top 200

A frequency list ranks words by how often they appear in a corpus of texts. For Latin, frequency lists are among the most powerful learning tools available, because a small number of words accounts for a large share of any text. This page covers the science behind frequency learning, the major lists, the top words by category, and practical acquisition strategies. 1. What a Frequency List Is and How to...
latin vocabulary frequency dcc May 30, 2026
Programming › Algorithm Cookbook › Chapter 5. Hashing and Maps ›

5.8 Counting Maps

5.8 Counting Maps Problem You need to count how many times each key appears in a dataset. A standard map stores one value per key. In counting problems, the value is a frequency. The task is to update counts efficiently while scanning input once. Solution Use a map from key to integer count. freq: Map<Key, Int> For each key, read the current count, then increment. count(items): freq = empty map...
algorithms hashing counting frequency maps May 4, 2026
Wiki › Algorithms › 01. Searching and Sorting › 5. Selection and Order Statistics ›

Count Min Sketch Query

Count Min Sketch Query Count Min Sketch is a probabilistic data structure for estimating item frequencies in a stream. It stores counts in a small two dimensional table and uses several hash functions to update and query the table. It gives approximate answers with one-sided error: the estimated count is never below the true count, but it may be above it because of hash collisions. Problem Given a stream $$...
algorithms streaming frequency count-min-sketch approximate
Wiki › Algorithms › 01. Searching and Sorting › 5. Selection and Order Statistics ›

Misra Gries

Misra Gries Misra Gries is a deterministic streaming algorithm for finding frequent items with bounded memory. It keeps at most $k - 1$ counters and returns a small candidate set that contains every item whose frequency is greater than $n/k$. The algorithm may return extra candidates. A second pass gives exact frequencies and removes false positives. Problem Given a stream $$ x_1, x_2, \dots, x_n $$ and an integer $k...
algorithms streaming heavy-hitters frequency
Wiki › Algorithms › 01. Searching and Sorting › 1. Linear and Sequential Search ›

Frequency Count

Frequency Count Search Frequency count search computes how many times a target value appears in a sequence. It performs a full scan and increments a counter whenever a match occurs. This is a basic aggregation primitive used in statistics, histograms, and preprocessing. Problem Given a sequence $A$ of length $n$ and a value $x$, compute $$ \text{count}(x) = |{, i \mid 0 \le i < n,\ A[i] = x ,}|...
algorithms searching frequency
Wiki › Algorithms › 01. Searching and Sorting › 5. Selection and Order Statistics ›

Streaming Heavy Hitters

Streaming Heavy Hitters Streaming Heavy Hitters finds items that occur frequently in a stream. The stream may be too large to store, so the algorithm keeps only a compact summary. The usual goal is to report all values whose frequency is above a threshold, or to estimate the most frequent values. Problem Given a stream $$ x_1, x_2, \dots, x_n $$ find items whose frequency is large compared with $n$....
algorithms selection streaming heavy-hitters frequency