# The CQC Algorithm: Cycling in Graphs to Semantically Enrich and Enhance a Bilingual Dictionary

arXiv: https://arxiv.org/abs/1402.2561 · HTML: https://mlsanity.com/paper/1402.2561/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jan 2014.

## Built on by (most cited first, 2 of 2)

- [A Benchmark and Scoring Algorithm for Enriching Arabic Synonyms](https://mlsanity.com/paper/2302.02232/) (2023)
- [Current Trends and Approaches in Synonyms Extraction: Potential Adaptation to Arabic](https://mlsanity.com/paper/2205.10412/) (2022)

## Abstract (arXiv)

Bilingual machine-readable dictionaries are knowledge resources useful in many automatic tasks. However, compared to monolingual computational lexicons like WordNet, bilingual dictionaries typically provide a lower amount of structured information, such as lexical and semantic relations, and often do not cover the entire range of possible translations for a word of interest. In this paper we present Cycles and Quasi-Cycles (CQC), a novel algorithm for the automated disambiguation of ambiguous translations in the lexical entries of a bilingual machine-readable dictionary. The dictionary is represented as a graph, and cyclic patterns are sought in the graph to assign an appropriate sense tag to each translation in a lexical entry. Further, we use the algorithms output to improve the quality of the dictionary itself, by suggesting accurate solutions to structural problems such as misalignments, partial alignments and missing entries. Finally, we successfully apply CQC to the task of synonym extraction.