International Business Machines Corporation

Language Analysis Systems, Inc.

Leonard Arthur Shaefer, Jr

Frankie Elizabeth Patman Maguire

Richard Theodore Gillam

Charles Kinston Williams

Frank Everett Whaley

John Christian Hermansen

Heather McCallum-Bayliss

Richard D Lutz

Stephen John Watjen

David Edward Biesenbach

Anna Khasin

Friederike Mallchok

According to one embodiment of the present invention, a method for name searching in mixed-entity lists is provided which comprises dividing a mixed list of entities into a plurality of entity-specific lists. A name to be searched is then categorized into a category and a specialized search logic is applied to the name to be searched. The specialized search logic is selected to be adapted to the category and uses a one of the entity-specific lists that corresponds to the category of the name to be searched. A shared search logic may also be employed, which is used for all names to be searched.

Entity-driven logic for improved name-searching in mixed-entity lists

Provided are techniques for parsing a name. A name to be parsed is received. A culture of the name is identified. One or more name phrases from the name are identified. Statistics for the one or more name phrases are identified. It is determined whether to perform a first parsing technique that parses different types of name elements within at least one field of the name. In response to determining that the first parsing technique is to be performed, the name is parsed using the statistics and the first parsing technique. In response to determining that the first parsing technique is not to be performed, the name is parsed using the statistics and a second parsing technique.

Parsing culturally diverse names

Provided are techniques for identifying related names. A collection of names from different languages is stored, wherein each of the names has a native orthographic form and a romanized form. An input name is received in a known encoding scheme. An alphabet of the input name is determined based on the known encoding scheme. One or more romanized names are generated based on the query name and the determined query name alphabet. Culture-sensitive regularization rules are applied to create an additional romanized name. The one or more romanized names and the additional romanized name are matched against the romanized names in the collection of names from the different languages. Data store records that have romanized names that match the one or more romanized names or the additional romanized name are returned.

Identifying related names

An automated name searching system incorporates an automatic name classifier and a multi-path architecture in which different algorithms are applied based on cultural identity of the query name. The name classifier operates with a preemptive list, analysis of morphological elements, length, and linguistic rules. A name regularizer produces a character based computational representation of the name. A pronunciation equivalent representation such as an IPA language representation, and language specific rules to generate name searching keys, are used in a first pass to eliminate database entries which are obviously not matches for the query name. The methods can also be implemented as a callable set of library routines including an intelligent preprocessor and a name evaluator that produces a score comparing a query name and database name, based on a variety of user-adjustable parameters. The user-controlled parameters permit tuning of the search methodologies for specific custom applications.

System for adaptive multi-cultural searching and matching of personal names

A method and system for differentiating types of data stored in a data collection. In one implementation, the method includes receiving a search request on a first type of data stored in the data collection; automatically differentiating data of the first type stored in the data collection from data of other types stored in the data collection; and completing the search request using data determined to be of the first type. Automatically differentiating data of the first type includes determining a type of each data entry in the data collection based only on tokens associated with the data entry.

Method and apparatus for automatically differentiating between types of names stored in a data collection

A method and system for performing a search request for a name among a database including a plurality of names. In one implementation, the method includes receiving the search request on the name, determining a geographic location associated with the name, assigning a cultural classification to the name based on the geographic location associated with the name, and completing the search request by searching for the name among the plurality of names within the database based on the cultural classification assigned to the name.

Method and apparatus for assigning a cultural classification to a name using country-of-association information

A system and method for improved name matching using regularized name forms is presented. A regularization rule engine uses culture-specific regularization rules to iteratively convert candidate names and query names to a canonical form, which are regularized candidate names and regularized query names, respectively. The regularization rules are context-sensitive or context-free rules that pertain to a name's originating culture. Subsequently, a name search engine compares the regularized query name with the regularized candidate names and identifies the regularized candidate names that meet a particular regularization matching threshold. In turn, name search engine selects the candidate names that correspond to the identified regularized candidate names and provides the selected candidate names to a user.

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Leesburg, VA, United States of America

Leonard Arthur Shaefer, Jr