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US 8,275,600 B2Granted
Machine learning for transliteration
AssigneeGoogle Inc.
InventorsSlaven Bilac, Hiroshi Ichikawa
Life of this patent
Estimating the term…
Abstract
Methods, systems, and apparatus, including computer program products, for automatically identifying transliteration pairs are disclosed. In one implementation, a method is provided. The method includes receiving a plurality of resources, the plurality of resources including a plurality of anchor text; determining one or more potential transliterations from the plurality of anchor text; and identifying one or more potential transliteration pairs from the one or more potential transliterations, where each potential transliteration pair includes a first anchor text in a first writing system and a second anchor text in a second writing system, the second anchor text and the first anchor text identifying a same resource or location.
Claims22
A method comprising:
- receiving a plurality of resources, the plurality of resources including a plurality of anchor text, wherein anchor text found in a specific resource of the plurality of resources links to a different resource identified by a uniform resource locator of the different resource;
- determining one or more potential transliterations from the plurality of anchor text;
- sorting the one or more potential transliterations, based on likelihoods of the one or more potential transliterations co-occurring with text that identifies a same resource or location;
- identifying one or more potential transliteration pairs from the one or more potential transliterations, wherein each potential transliteration pair includes a first anchor text in a first writing system and a second anchor text in a second writing system, the second anchor text and the first anchor text linking to a same resource;
- for each potential transliteration pair,
- comparing the first anchor text and the second anchor text;
- and
- first classifying the potential transliteration pair as being a transliteration pair or not being a transliteration pair, based on the comparison;
- first sorting the first classified potential transliteration pairs, based on likelihoods of the first classified potential transliteration pairs being transliteration pairs, to produce first sorted potential transliteration pairs;
- identifying a subset of the first sorted potential transliteration pairs, the subset including potential transliteration pairs classified as being transliteration pairs and potential transliteration pairs classified as not being transliteration pairs;
- for each potential transliteration pair in the subset,
- aligning the first anchor text and the second anchor text;
- and
- extracting one or more edits from the alignment;
- generating a classification model, based on the one or more edits and the subset;
- and
- second classifying each of the first classified potential transliteration pairs as being a transliteration pair or not being a transliteration pair, using the classification model.
14 more elements
A method comprising:
- receiving a plurality of resources, the plurality of resources including a plurality of anchor text, wherein anchor text found in a specific resource of the plurality of resources links to a different resource identified by a uniform resource locator of the different resource;
- determining one or more potential transliterations from the plurality of anchor text;
- identifying one or more potential transliteration pairs from the one or more potential transliterations, wherein each potential transliteration pair includes a first anchor text in a first writing system and a second anchor text in a second writing system, the second anchor text and the first anchor text linking to a same resource;
- for each potential transliteration pair,
- classifying the potential transliteration pair as being a transliteration pair or not being a transliteration pair;
- aligning the first anchor text with the second anchor text;
- and
- extracting one or more edits from the alignment;
- and
- generating a classification model, based on the one or more edits and a subset of the classified potential transliteration pairs.
7 more elements
A computer program product, encoded on a computer readable storage medium, operable to cause one or more processors to perform operations comprising:
- receiving a plurality of resources, the plurality of resources including a plurality of anchor text, wherein anchor found in a specific resource of the plurality of resources links to a different resource identified by a uniform resource locator of the different resource;
- determining one or more potential transliterations from the plurality of anchor text;
- identifying one or more potential transliteration pairs from the one or more potential transliterations, wherein each potential transliteration pair includes a first anchor text in a first writing system and a second anchor text in a second writing system, the second anchor text and the first anchor text linking to a same resource;
- for each potential transliteration pair,
- classifying the potential transliteration pair as being a transliteration pair or not being a transliteration pair;
- aligning the first anchor text with the second anchor text;
- and
- extracting one or more edits from the alignment;
- and
- generating a classification model, based on the one or more edits and a subset of the classified potential transliteration pairs.
7 more elements
A system comprising:
- a machine readable storage device including a program product;
- and
- one or more computers operable to execute the program product and perform operations comprising:
- receiving a plurality of resources, the plurality of resources including a plurality of anchor text, wherein anchor text found in a specific resource of the plurality of resources links to a different resource identified by a uniform resource locator of the different resource;
- determining one or more potential transliterations from the plurality of anchor text;
- identifying one or more potential transliteration pairs from the one or more potential transliterations, wherein each potential transliteration pair includes a first anchor text in a first writing system and a second anchor text in a second writing system, the second anchor text and the first anchor text linking to a same resource;
- for each potential transliteration pair,
- classifying the potential transliteration pair as being a transliteration pair or not being a transliteration pair;
- aligning the first anchor text with the second anchor text;
- and
- extracting one or more edits from the alignment;
- and
- generating a classification model, based on the one or more edits and a subset of the classified potential transliteration pairs.
10 more elements
Dependencies are inferred from the claim text.