Abstract: We have invented a process and method for creating a general-purpose adaptive or static machine-learning classifier using prediction by partial matching (PPM) language modeling. This classifier can incorporate homogeneous or heterogeneous feature types; variable-size contexts; sequential or non-sequential features. Features are ordered (linearized) by information saliency; and truncation of least-informative context is used for backoff to handle previously unseen events. Labels may be endogenous (from within the group) or exogenous (outside the group) of the feature types. Classification may generate labels and their probabilities; or only labels. Classification stores may be complete or minimized where redundant states are removed producing significant space savings and performance improvements. Classifiers may be static (unchanging) or online (adaptive or updatable incrementally or in batch). PPM classifiers may be incorporated in ensembles of other PPM classifiers or different machine learning algorithms.

Abstract: We describe here a system and method for creating, maintaining and using a semantic search engine environment for precise retrieval of curated answers to questions where the answers may be drawn from an authoritative document collection. The invention combines processing by human developers and software: semantic editing tools for creating, storing, maintaining queries and variants of queries, and query and document passage categories; links from queries to text passages that provide answers to these queries; a document retrieval store; means for matching user queries against stored queries; means for creating, storing, maintaining, and retrieving semantic and management metadata and categories about queries and documents and using these data for navigating the document collection; and means for finding information related to the user's information need by text and semantic similarity retrieval.

Abstract: The present invention relates to an apparatus system and method for creating a customizable and application-specific semantic similarity utility that uses a single similarity measuring algorithm with data from broad-coverage structured lexical knowledge bases (dictionaries and thesauri) and corpora (document collections). More specifically the invention includes the use of data from custom or application-specific structured lexical knowledge bases and corpora and semantic mappings from variant expressions to their canonical forms. The invention uses a combination of technologies to simplify the development of a generic semantic similarity utility; and minimize the effort and complexity of customizing the generic utility for a domain- or topic-dependent application. The invention makes customization modular and data-driven, allowing developers to create implementations at varying degrees of customization (e.g., generic, domain-level, company-level, application-level) and also as changes occur over time (e.g.

Abstract: We describe here a system and method for creating, maintaining and using a semantic search engine environment for precise retrieval of curated answers to questions where the answers may be drawn from an authoritative document collection. The invention combines processing by human developers and software: semantic editing tools for creating, storing, maintaining queries and variants of queries, and query and document passage categories; links from queries to text passages that provide answers to these queries; a document retrieval store; means for matching user queries against stored queries; means for creating, storing, maintaining, and retrieving semantic and management metadata and categories about queries and documents and using these data for navigating the document collection; and means for finding information related to the user's information need by text and semantic similarity retrieval.

Abstract: The present invention relates to an apparatus system and method for creating a customizable and application-specific semantic similarity utility that uses a single similarity measuring algorithm with data from broad-coverage structured lexical knowledge bases (dictionaries and thesauri) and corpora (document collections). More specifically the invention includes the use of data from custom or application-specific structured lexical knowledge bases and corpora and semantic mappings from variant expressions to their canonical forms. The invention uses a combination of technologies to simplify the development of a generic semantic similarity utility; and minimize the effort and complexity of customizing the generic utility for a domain- or topic-dependent application. The invention makes customization modular and data-driven, allowing developers to create implementations at varying degrees of customization (e.g., generic, domain-level, company-level, application-level) and also as changes occur over time (e.g.

Abstract: We describe here a system and method for creating, maintaining and using a semantic search engine environment for precise retrieval of curated answers to questions where the answers may be drawn from an authoritative document collection. The invention combines processing by human developers and software: semantic editing tools for creating, storing, maintaining queries and variants of queries, and query and document passage categories; links from queries to text passages that provide answers to these queries; a document retrieval store; means for matching user queries against stored queries; means for creating, storing, maintaining, and retrieving semantic and management metadata and categories about queries and documents and using these data for navigating the document collection; and means for finding information related to the user's information need by text and semantic similarity retrieval.

Abstract: We have invented a process and method for creating a general-purpose adaptive or static machine-learning classifier using prediction by partial matching (PPM) language modeling. This classifier can incorporate homogeneous or heterogeneous feature types; variable-size contexts; sequential or non-sequential features. Features are ordered (linearized) by information saliency; and truncation of least-informative context is used for backoff to handle previously unseen events. Labels may be endogenous (from within the group) or exogenous (outside the group) of the feature types. Classification may generate labels and their probabilities; or only labels. Classification stores may be complete or minimized where redundant states are removed producing significant space savings and performance improvements. Classifiers may be static (unchanging) or online (adaptive or updatable incrementally or in batch). PPM classifiers may be incorporated in ensembles of other PPM classifiers or different machine learning algorithms.

Abstract: We describe here a system and method for creating, maintaining and using a semantic search engine environment for precise retrieval of curated answers to questions where the answers may be drawn from an authoritative document collection. The invention combines processing by human developers and software: semantic editing tools for creating, storing, maintaining queries and variants of queries, and query and document passage categories; links from queries to text passages that provide answers to these queries; a document retrieval store; means for matching user queries against stored queries; means for creating, storing, maintaining, and retrieving semantic and management metadata and categories about queries and documents and using these data for navigating the document collection; and means for finding information related to the user's information need by text and semantic similarity retrieval.

Abstract: We have discovered a system and method for improving the quality of information extraction applications consisting of an ensemble of per-user, adaptive, on-line machine-learning classifiers that adapt to document content and judgments of users by continuously incorporating feedback from information extraction results and corrections that users apply to these results. The satellite classifier ensemble uses only the immediately available features for classifier improvement and it is independent of the complex cascade of earlier decisions leading to the final information extraction result. The machine-learning classifiers may also provide explanations or justifications for classification decisions in the form of rules, other machine-learning classifiers may provide feedback in the form of supporting instances or patterns.

Abstract: A semantic discovery and exploration system is disclosed where an environment enabling a developer or user to uncover, navigate, and organize semantic patterns and structures in a document collection with or without the aid of structured knowledge. The semantic discovery and exploration system provides techniques for searching document collections, categorizing documents, inducing lists of related concepts, and identifying clusters of related terms and documents. This system operates both without and with infusions of structured knowledge such as gazetteers, thesauruses, taxonomies and ontologies. System performance improves when structured knowledge is incorporated. The semantic discovery and exploration system may be used as a first step in developing an information extraction system such as to categorize or cluster documents in a particular domain or to develop gazetteers and as a part of a deployed run-time information extraction system.

Abstract: We have discovered a system and method for improving the quality of information extraction applications consisting of an ensemble of per-user, adaptive, on-line machine-learning classifiers that adapt to document content and judgments of users by continuously incorporating feedback from information extraction results and corrections that users apply to these results. The satellite classifier ensemble uses only the immediately available features for classifier improvement and it is independent of the complex cascade of earlier decisions leading to the final information extraction result. The machine-learning classifiers may also provide explanations or justifications for classification decisions in the form of rules, other machine-learning classifiers may provide feedback in the form of supporting instances or patterns.

Abstract: A semantic discovery and exploration system is disclosed where an environment enabling a developer or user to uncover, navigate, and organize semantic patterns and structures in a document collection with or without the aid of structured knowledge. The semantic discovery and exploration system provides techniques for searching document collections, categorizing documents, inducing lists of related concepts, and identifying clusters of related terms and documents. This system operates both without and with infusions of structured knowledge such as gazetteers, thesauruses, taxonomies and ontologies. System performance improves when structured knowledge is incorporated. The semantic discovery and exploration system may be used as a first step in developing an information extraction system such as to categorize or cluster documents in a particular domain or to develop gazetteers and as a part of a deployed run-time information extraction system.

Abstract: A filter includes at least two different adsorptive media. First, chemisorptive media, which is porous and includes an acidic functional group, is used to remove molecular bases, including ammonia, organic amines, imides and aminoalchols, from the atmosphere used in semiconductor fabrication and other processes that require uncontaminated gaseous environments of high quality. Second, physisorptive media is able to adsorb condensable contaminants, particularly those having a boiling point greater than 150 degrees C. The physisorptive media can include untreated, activated carbon.

Abstract: The present invention relates to a system and method for sampling a gas flow to measure one or more contaminants within a semiconductor processing tool. The system includes a portable unit containing one or more dry traps, Tenax traps and, if desired, wet impingers. The unit is coupled to a gas flow in a clean room and the dry traps. Tenax traps and wet impingers measure contaminants contained in the gas supply for a determined sampling interval. When the sampling interval is done, the unit is sent to an analysis facility for processing.

Abstract: A detection system for detecting base contamination at low concentrations in gas, for instance to protect a sensitive process, characterized in that the detection system in constructed to examine multiple amines in gas to produce a reading stoichiometrically related to the proton bonding characteristic of the multiple amines present, the detection system comprising at least two channels through which a gas to be examined passes, an amines remover located in one of the channels, at least one thermal/catalytic converter which discharges NO for each channel, and at least one chemiluminescent NO detector, whereby the total amine concentration is determined from the difference between the detected signals for the channels.

Abstract: The present invention relates to systems and methods for controlling humidity and temperature in gases or air streams used in semiconductor processing systems. These systems and methods can be used in combination with systems and methods for contaminant detection and removal.

Abstract: A filter includes at least two different adsorptive media. First, chemisorptive media, which is porous and includes an acidic functional group, is used to remove molecular bases, including ammonia, organic amines, imides and aminoalchols, from the atmosphere used in semiconductor fabrication and other processes that require uncontaminated gaseous environments of high quality. Second, physisorptive media is able to adsorb condensable contaminants, particularly those having a boiling point greater than 150 degrees C. The physisorptive media can include untreated, activated carbon.

Abstract: In preferred embodiments, the invention provides a gas filter for a reactive gas used in semiconductor processing tools and processes that are sensitive to molecular contamination. The reactive gas filters of the invention have improved pressure drop and can supply an output gas stream having concentrations of less than about 1 ppbv for both ammonia and sulfur dioxide for an input gas stream with ammonia and sulfur dioxide concentrations, respectively, of no greater than about 10 ppbv and 5 ppbv. In one aspect the invention provides a reactive gas filter with an improved pressure drop that can supply an output gas stream having concentrations of less than about 1 ppbv for both ammonia and sulfur dioxide for an input gas stream with ammonia and sulfur dioxide concentrations, respectively, of no greater than about 10 ppbv and 5 ppbv, using a filter media volume of no greater than about 0.5 litters.

Abstract: A detection system for detecting contaminant gases includes a converter, a detector, a primary channel for delivering a target gas sample through the converter to the detector, and at least two scrubbing channels for delivering a reference gas sample through the converter to the detector. Each of the scrubbing channels includes a scrubber for removing basic nitrogen compounds from the reference gas sample, while the primary channel preferably transmits the target gas sample without scrubbing. The converter converts gaseous nitrogen compounds in the target gas sample to an indicator gas, such as nitric oxide (NO), and a control system directs the flow of a gas sample among the primary channel and the scrubbing channels. In accordance with one aspect of the invention, the basic-nitrogen-compound concentration can be measured by comparing the concentration of the indicator gas detected in the reference sample with the detected indicator-gas concentration in the target sample.

Abstract: The present invention provides passive sampling systems and methods for monitoring contaminants in a semiconductor processing system. In one embodiment, that passive sampling system comprises a collection device in fluid communication with a sample line that provides a flow of gas from a semiconductor processing system. The collection device is configured to sample by diffusion one or more contaminants in the flow of gas.