Abstract: Adaptive navigation techniques are disclosed that allow navigation systems to learn from a user's personal driving history. As a user drives, models are developed and maintained to learn or otherwise capture the driver's personal driving habits and preferences. Example models include road speed, hazard, favored route, and disfavored route models. Other attributes can be used as well, whether based on the user's personal driving data or driving data aggregated from a number of users. The models can be learned under explicit conditions (e.g., time of day/week, driver ID) and/or under implicit conditions (e.g., weather, drivers urgency, as inferred from sensor data). Thus, models for a plurality of attributes can be learned, as well as one or more models for each attribute under a plurality of conditions. Attributes can be weighted according to user preference. The attribute weights and/or models can be used in selecting a best route for user.

Abstract: In one embodiment, a system and method for charting audible choices comprises determining if an option is offered; selecting the option if the option is offered; and saving a result, wherein the result is associated with the selected option.

Abstract: Adaptive navigation techniques are disclosed that allow navigation systems to learn from a user's personal driving history. As a user drives, models are developed and maintained to learn or otherwise capture the driver's personal driving habits and preferences. Example models include road speed, hazard, favored route, and disfavored route models. Other attributes can be used as well, whether based on the user's personal driving data or driving data aggregated from a number of users. The models can be learned under explicit conditions (e.g., time of day/week, driver ID) and/or under implicit conditions (e.g., weather, drivers urgency, as inferred from sensor data). Thus, models for a plurality of attributes can be learned, as well as one or more models for each attribute under a plurality of conditions. Attributes can be weighted according to user preference. The attribute weights and/or models can be used in selecting a best route for user.

Abstract: Adaptive navigation techniques are disclosed that allow navigation systems to learn from a user's personal driving history. As a user drives, models are developed and maintained to learn or otherwise capture the driver's personal driving habits and preferences. Example models include road speed, hazard, favored route, and disfavored route models. Other attributes can be used as well, whether based on the user's personal driving data or driving data aggregated from a number of users. The models can be learned under explicit conditions (e.g., time of day/week, driver ID) and/or under implicit conditions (e.g., weather, drivers urgency, as inferred from sensor data). Thus, models for a plurality of attributes can be learned, as well as one or more models for each attribute under a plurality of conditions. Attributes can be weighted according to user preference. The attribute weights and/or models can be used in selecting a best route for user.

Abstract: Adaptive navigation techniques are disclosed that allow navigation systems to learn from a user's personal driving history. As a user drives, models are developed and maintained to learn or otherwise capture the driver's personal driving habits and preferences. Example models include road speed, hazard, favored route, and disfavored route models. Other attributes can be used as well, whether based on the user's personal driving data or driving data aggregated from a number of users. The models can be learned under explicit conditions (e.g., time of day/week, driver ID) and/or under implicit conditions (e.g., weather, drivers urgency, as inferred from sensor data). Thus, models for a plurality of attributes can be learned, as well as one or more models for each attribute under a plurality of conditions. Attributes can be weighted according to user preference. The attribute weights and/or models can be used in selecting a best route for user.

Abstract: A method including enumerating plausible queries of a target database using query generation rules, and generating associated teasers for each of the enumerated queries using query matching rules.

Abstract: A measure of the usefulness of an item in a collection of information with respect to a first set of one or more criteria is determined. A first measure of the usefulness of the item with respect to the first set of criteria is determined. A measure of the quality of the item is determined. A second measure of usefulness based on the first measure of usefulness and the measure of quality is determined.

Abstract: A method including enumerating plausible queries of a target database using query generation rules, and generating associated teasers for each of the enumerated queries using query matching rules.

Abstract: A popularity predicting process for determining the popularity of a text-based object includes a query analysis process for analyzing a query to determine a plurality of links to Internet objects relating to the query. A link weighting process determines the individual link strength of each of the plurality of links, thus generating a plurality of link strengths. A link strength summing process determines the sum of the plurality of link strengths, wherein the sum corresponds to the popularity of the text-based object.

Abstract: A wearable device is configured for navigating in an indoor environment. The device includes passive sensors for measuring environmental physical conditions at known locations in the indoor environment and at an unknown locations in the indoor environment. A wearable computer is coupled to passive sensors. The computer is configured to construct a first statistical model of the environment according to the measured physical conditions at the known locations and a second statistical model of the environment according to the measured physical conditions at the unknown locations. Processing means of the computer determines a probability that the unknown locations correspond to the known locations by comparing the second statistical model to the first statistical model.

Abstract: A system is provided which translates phrases from a source language to a target language, and which includes means for continually updating the set of phrases that are known and translatable by the system so as to ensure that the set of phrases accurately reflects the sentences that users most frequently ask to have translated.

Abstract: A system is provided for correcting users' mistakes including context-sensitive spelling errors and the like in which an adaptive correction algorithm is utilized which is trained on not only a conventional training corpus, but also on the text which is being corrected, thus to permit the correction of words based on the particular usages of the words in the text being corrected, taking advantage of the fact that the text to be corrected is by and large already mostly correct.

Abstract: A system located in an automobile provides personalized traffic information nd route planning capabilities. This system uses equipment which is becoming standard in automobiles, such as on-board navigation systems and cellular telephones. On-board navigation systems use global positioning system (GPS) satellites to position the automobile with respect to streets in a map database. As the automobile moves, the navigation system updates the location. A central database includes travel time information for each street segment and transition between street segments in the map database. Based upon the travel time information in the database, a route from a current location to a desired destination, or series of destinations, can be planned in order to have a minimum travel time. The route can be provided to the on-board navigation system, which then directs the driver in traveling the route.

Abstract: A context-based dictionary entry access system includes selecting and rang an entry based on the part-of-speech assigned to the given word in a sentence. The entries corresponding to the word in context are first selected, followed by availability of entries that are not relevant to the current context. The part of speech of the given word in context is selected based on the utilization of a part-of-speech tagger such that only those entries are selected in which the corresponding word makes syntactic sense in the sentence.

Abstract: In a grammar checking system in which a sentence is first tagged as to pa of speech, the probability of the sequence of the parts of speech being correct is utilized to correct improper use of troublesome words, especially those identical sounding words which are spelled differently. The system corrects word usage based not on the probability of the entire sentence being correct but rather on the probability of the sequence of the parts of speech being correct. As part of the subject invention, the parts of speech sequence probability is utilized in part of speech sequence verification, underlying spelling recovery, auxiliary verb correction, determiner correction, and in a context-sensitive dictionary lookup.

Abstract: A system is provided for spelling correction in which the context of a word n a sentence is utilized to determine which of several alternative or possible words was intended. The probability that a particular alternative was the word that was intended is determined through Bayesian analysis utilizing multiple kinds of features of the context of the target word, such as the presence of certain characteristic words within some distance of the target word, or the presence of certain characteristic patterns of words and part-of-speech tags around the target word. The system successfully combines multiple types of features via Bayesian analysis through means for resolving egregious interdependencies among features. The system first recognizes the interdependencies, and then resolves them by deleting all but the strongest feature involved in each interdependency, thereby allowing it to make its decisions based on the strongest non-conflicting set of features.

Abstract: In a grammar checking system in which a sentence is first tagged as to parts of speech, the probability of the sequence of the parts of speech being correct is utilized to correct improper use of troublesome words, especially those identical sounding words which are spelled differently. The system corrects word usage based not on the probability of the entire sentence being correct but rather on the probability of the sequence of the parts of speech being correct. As part of the subject invention, the parts of speech sequence probability is utilized in part of speech sequence verification, underlying spelling recovery, auxiliary verb correction, determiner correction, and in a context-sensitive dictionary lookup.

Abstract: In a grammar checking system which includes first tagging a sentence as to parts of speech, a module is provided for correcting incorrect auxiliary verb sequences involving two or more verbs by first detecting the starting and ending points of the error and then correcting the indicated verbs through the utilization of a directed acyclic graph containing the set of correct auxiliary verb sequences constructed for all possible such sequences. Thereafter, a further directed graph functions as a finite state transducer for proposing corrections for incorrect auxiliary verb sequences as determined by the aforementioned acyclic graph of incorrect verb sequences.

Abstract: In a grammar checking system which includes first tagging a sentence as to parts of speech and recovery of underlying spellings, a system for the correction of inflections includes identifying typical example of words which do not follow normal rules either as to pluralization, past tense, past participle, comparative formation and superlative formation, with this unique list of incorrect words forming the basis for suggesting suitable replacement words the system first performs a conventional spell check to detect mispellings by dictionary lookup system. Thereafter correct words are suggested based on an English dictionary and on the root forms and the morphological features derived from the incorrect words in the compendium.

Abstract: In a grammar checking system which includes first tagging a sentence as to parts of speech, underlying spelling is recovered by removing the effects of capitalization of a word so that appropriate inflection and or spelling can be suggested by the system. In order to determine the underlying spelling the system determines whether a noun is a proper noun through the utilization of a part of speech tagger and the utilization of part of speech trigram probabilities, with capitalized and uncapitalized versions of the word having different trigram probabilities. The system also establishes whether a word is an ordinary word as opposed to a proper noun or other intrinsically capitalized word. With the system further determining which of two interpretations of the word is the best one.