Abstract: A data normalization system is described herein that represents multiple data types that are common within database systems in a normalized form that can be processed uniformly to achieve faster processing of data on superscalar CPU architectures. The data normalization system includes changes to internal data representations of a database system as well as functional processing changes that leverage normalized internal data representations for a high density of independently executable CPU instructions. Because most data in a database is small, a majority of data can be represented by the normalized format. Thus, the data normalization system allows for fast superscalar processing in a database system in a variety of common cases, while maintaining compatibility with existing data sets.

Abstract: The present invention relates to an integrated full-text search architecture that integrates full text search with database server applications in a tight manner so that it becomes part of the server in all aspects including storage, metadata, query processing, back/up restore and resource management. This provides improved performance with respect to queries as well as improved manageability. Furthermore, the subject architecture is open and schema directed unlike other conventional full-text search architectures. Accordingly, the full-text search architecture enables expert users (e.g., search providers) to define their own index structures as well as ranking algorithms.

Abstract: Detailed herein is a technology which, among other things, allows a search engine to utilize a user-defined relevance function. In one approach to the technology, a method of applying a user-defined relevance function is described. In this approach, a complex search query is decomposed into a simple operator. The simple operator is associated with the user-defined relevance function. A document which matches the search query is retrieved, and a rank is calculated for the document, using the user-defined relevance function.

Abstract: The subject invention pertains to database reverse query matching. A text document can be received and analyzed to determine which, if any, queries the document matches. To enable such functionality, a number of intermediate structures such as tables are generated in accordance with designated queries. In particular, a canonical table can be generated that specifies the expressions or phrases as well as match rules. Furthermore, a Boolean table can be generated that specifies the Boolean relationship of expressions in canonical table. A match component or methodology can match text phrases to query phrases identified by the canonical table. An evaluation component or related methodology can subsequently utilize the Boolean table to determine if the preliminary phrase matches match the query logic.

Abstract: The present invention relates to an integrated full-text search architecture that integrates full text search with database server applications in a tight manner so that it becomes part of the server in all aspects including storage, metadata, query processing, back/up restore and resource management. This provides improved performance with respect to queries as well as improved manageability. Furthermore, the subject architecture is open and schema directed unlike other conventional full-text search architectures. Accordingly, the full-text search architecture enables expert users (e.g., search providers) to define their own index structures as well as ranking algorithms.

Abstract: Detailed herein is a technology which, among other things, allows a search engine to utilize a user-defined relevance function. In one approach to the technology, a method of applying a user-defined relevance function is described. In this approach, a complex search query is decomposed into a simple operator. The simple operator is associated with the user-defined relevance function. A document which matches the search query is retrieved, and a rank is calculated for the document, using the user-defined relevance function.

Abstract: The present invention relates to an integrated full-text search architecture that integrates full text search with database server applications in a tight manner so that it becomes part of the server in all aspects including storage, metadata, query processing, back/up restore and resource management. This provides improved performance with respect to queries as well as improved manageability. Furthermore, the subject architecture is open and schema directed unlike other conventional full-text search architectures. Accordingly, the full-text search architecture enables expert users (e.g., search providers) to define their own index structures as well as ranking algorithms.

Abstract: The subject disclosure pertains to systems and methods for facilitating item retrieval and/or ranking. An original ranking of items can be modified and enhanced utilizing a Markov Random Field (MRF) approach based upon item similarity. Item similarity can be measured utilizing a variety of methods. An MRF similarity model can be generated by measuring of similarity between items. An original ranking of items can be obtained, where each document is evaluated independently based upon a query. For example, the original ranking can be obtained using a keyword search. The original ranking can be enhanced based upon similarity of items. For example, items that are deemed to be similar should have similar rankings. The MRF model can be used in conjunction with original rankings to adjust rankings to reflect item relationships.

Abstract: The subject invention pertains to database reverse query matching. A text document can be received and analyzed to determine which, if any, queries the document matches. To enable such functionality, a number of intermediate structures such as tables are generated in accordance with designated queries. In particular, a canonical table can be generated that specifies the expressions or phrases as well as match rules. Furthermore, a Boolean table can be generated that specifies the Boolean relationship of expressions in canonical table. A match component or methodology can match text phrases to query phrases identified by the canonical table. An evaluation component or related methodology can subsequently utilize the Boolean table to determine if the preliminary phrase matches match the query logic.

Abstract: The present invention relates to an integrated full-text search architecture that integrates full text search with database server applications in a tight manner so that it becomes part of the server in all aspects including storage, metadata, query processing, back/up restore and resource management. This provides improved performance with respect to queries as well as improved manageability. Furthermore, the subject architecture is open and schema directed unlike other conventional full-text search architectures. Accordingly, the full-text search architecture enables expert users (e.g., search providers) to define their own index structures as well as ranking algorithms.

Abstract: Consistency between the components used to generate and query a full-text index is determined and if a mismatch is detected, an error may be surfaced. A structure including information associated with each component used to build an index is programmatically compared with currently available components. The structure may be interrogated to enumerate the resources bound to a particular index. The enumeration of bound resources facilitates determination of what indexes (if any) must be regenerated for consistency as a result of a component upgrade or a move to another system.