International Business Machines Corporation

Sivan Yogev

Haggai Roitman

David Carmel

Einat Amitay

Elad Yom-Tov

Nadav Golbandi

Inbal Ronen

Dafna Sheinwald

Nadav Yosef Har'el

Benjamin Sznajder

Naama Zwerdling

Shila Ofek-Koifman

Erel Uziel

Method, system, and computer program product for access control for entity search are provided. The method includes: representing entity-relationship data in a conceptual model; representing entities in a search system as documents containing the entity's searchable content and metadata; defining authorization rules for searchers over entities and their relationships; and extending an entity document to include searchable tokens defining the authorization rules. Defining authorization rules may include: identifying query predicate constraints for entity search; and defining searchable tokens as paths for query predicates and permissible searchers; wherein the permissible searchers are permitted access to data based on a query that contains the predicate. Defining authorization rules may further include: defining searchable document files for a free-text predicate with a field name as a token of permissible searchers and the field value as the searchable content.

Access control for entity search

A method and system for providing relationships in search results are provided. The method includes indexing an entity in a search index as an entity index entry, the entity index entry including facets providing information on the entity type and related entities. Search results are obtained by a search engine in the form of ranked result entities, wherein the result entities include multiple types of entities. The method then includes retrieving index entries to determine relationships between search result entities and providing the relationships in search results. The method further includes, for each result entity, retrieving its entity index entry and cross-checking the facets of the retrieved entity index entry for other result entities.

Method and system for providing relationships in search results

Method, system, and computer program product for indexing and searching entity-relationship data are provided. The method includes: defining a logical document model for entity-relationship data including: representing an entity as a document containing the entity's searchable content and metadata; dually representing the entity as a document and as a category; and representing each relationship instance for the entity as a category set that contains categories of all participating entities in the relationship. The method also includes: translating entity-relationship data into the logical document model; and indexing the entity-relationship data of the populated logical document model as an inverted index. The method may include searching indexed entity-relationship data using a faceted search, wherein the categories are all categories required for supporting faceted navigation.

Indexing and searching entity-relationship data

Method, system, and computer program product for faceted search with relationships between categories are provided. The method includes: having a document set of multiple documents, each document having associated categories to which it belongs; grouping multiple categories associated with a document into a category set based on a relationship between the multiple categories; associating the category set with the document; and indexing the category set for retrieval of documents from categories sharing a category set. Wherein indexing the category set includes: having an index entry of a textual representations of a category, wherein the index entry includes a single occurrence for each document to which the category is attached; adding a payload to a document occurrence of a serialization of an identifier of the category sets to which the category belongs associated with the document. Indexing the category set further includes: adding an index entry for category set data, wherein the index entry includes a single occurrence for each document, wherein a document occurrence includes a payload of a serialization of an identifier of category sets associated with the document, and an identifier of the categories belonging to the category sets.

Faceted search with relationships between categories

A method for information retrieval with unified search between heterogeneous objects includes indexing a first object as a document in a search index; referencing a second object related to the first object in a facet of the document; and storing a relationship strength between the first and second objects in the facet of the document in the search index. Multiple heterogeneous objects can be related to the first object and referenced in multiple facets of the document, each with its relationship strength to the first object. Scoring an indirect object by indirect relation to a query object can be carried out by aggregating the relationship strengths between the indirect object and the retrieved objects multiplied by the retrieved objects' direct scores of relationship strength to the query object.

Information retrieval with unified search using multiple facets

A computer-implemented method for searching a corpus of documents includes defining a query as a twig including a root annotation operator having an associated tag specifying a span and having an associated expression indicative of one or more terms whose occurrence within the span will satisfy the query. An object is recursively selected from a group of objects that consists of the tag and the expression, and is used in advancing through the corpus until a candidate document is found that contains the tag and satisfies the expression. The candidate document is evaluated to determine whether the one or more terms indicated by the expression occur within the span in the candidate document so as to satisfy the annotation operator.

Object-oriented twig query evaluation

A method and system are provided for detection of authors across different types of information sources such as across documents on the Web. The method includes obtaining a compression signature for a document, and determining the similarity between compression signatures of two or more documents. If the similarity is greater than a threshold measure, the two or more documents are considered to be by the same author. Scored pairs of documents are clustered to provide a group of documents by the same author. The group of documents by the same author can be used for user profiling, noise reduction, contribution sizing, detecting fraudulent contributions, obtaining other search results by the same author, or mating a document with undisclosed authorship to a document of known author.

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Sivan Yogev