Abstract: In one embodiment, generating an ontology includes accessing an inverted index comprising a plurality of inverted index lists. An inverted index list may correspond to a term of a language. Each inverted index list may comprise a term identifier of the term and one or more document identifiers indicating one or more documents of a document set in which the term appears. The embodiment also includes generating a term identifier index according to the inverted index. The term identifier index comprises a plurality of sections and each section corresponds to a document. Each section may comprise one or more term identifiers of one or more terms that appear in the document.

Abstract: In one embodiment, determining a document specificity includes accessing a record that records the clusters of documents. The number of themes of a document is determined from the number of clusters of the document. The specificity of the document is determined from the number of themes.

Abstract: According to certain embodiments, a characteristic function representing data is received. A first hash code calculated from the characteristic function is received. The characteristic function is transformed to an arithmetic function. A second hash code is calculated from the arithmetic function. If the first hash code equals the second hash code, the data is designated as valid; otherwise, the data is designated as invalid.

Abstract: Construct a plurality of first binary decision diagrams (BDDs), each representing a different one of a plurality of words. Construct a plurality of second BDDs, each representing a different one of a plurality of search queries, each of the search queries comprising one or more of the words. Construct a plurality of third BDDs, each representing a different one of a plurality of web pages. Construct a plurality of fourth BDDs, each representing a different one of a plurality of search results, each search result comprising one or more web pages. Construct a plurality of fifth BDDs each representing a different one of a plurality of search tuples, each of the search tuples comprising a different one of the search queries and a different one of the search results. Construct a sixth BDD representing the search queries and the search results.

Abstract: In particular embodiments, a method includes receiving a query for data in data sets that are within a specified range, constructing a first binary decision diagram (BDD) representing the specified range, and constructing a third BDD representing the data in the specified range by performing an AND operation between the first BDD and a second BDD representing the data sets.

Abstract: In particular embodiments, a method includes receiving from a remote system a binary decision diagram (BDD) representing data streams from sensors, an input, and a first hash code, transforming the received BDD to a second arithmetic function by performing the arithmetic transformation on the received BDD, calculating a second hash code from the second arithmetic function and the input, and if the first hash code equals the second hash code, then indicating that the received BDD is uncorrupted data, else indicating that the received BDD is corrupted data.

Abstract: In particular embodiments, a method includes accessing a first binary decision diagram (BDD) representing a data stream from a first sensor and a second BDD representing a data stream from a second sensor, constructing a third BDD by performing an OR operation between the first and second BDDs, determining sizes of the first, second, and third BDDs, and if the third BDD is smaller than the sum of the first and second BDDs, then storing the third BDD, else storing the first and second BDDs.

Abstract: In particular embodiments, a method includes accessing first binary decision diagrams (BDDs) representing data streams from sensors, selecting portions from the first BDDs based on ease-of-analysis, and constructing a second BDD by performing an OR operation between the selected portions of the first BDDs.

Abstract: In particular embodiments, a method includes analyzing a binary decision diagram (BDD) representing a data stream from a sensor to determine a compression rate of the BDD and indicating a sensor malfunction in the sensor if the compression rate of the BDD deviates from a specified compression rate range.

Abstract: In particular embodiments, a method includes accessing a first binary decision diagram (BDD) representing data streams from sensors, selecting portions from the first BDD based on ease-of-analysis, and constructing a plurality of sub-BDDs by partitioning the first BDD, wherein the sub-BDDs comprises a first sub-BDD representing the selected portions, and second sub-BDDs representing the non-selected portions.

Abstract: In particular embodiments, a method includes accessing a first binary decision diagram (BDD) representing data streams from sensors, selecting portions from the first BDD, constructing a second BDD representing the selected portions and a third BDD representing the non-selected portions, determining sizes of the first, second, and third BDDs, and if the size of the first BDD is less than a sum of the sizes of the second and third BDDs, then storing the first BDD, else storing the second and third BDDs.

Abstract: In particular embodiments, a method includes receiving data sets, constructing a first binary decision diagram (BDD) representing the data sets, iteratively adding data from the data sets to the first BDD until a compression rate of the first BDD reaches a threshold compression rate, constructing a second BDD representing data from the data sets received after the compression rate of the first BDD equals a threshold compression rate, and iteratively adding data from the data sets to the second BDD.

Abstract: In particular embodiments, a method includes accessing a first binary decision diagram (BDD) representing data streams from sensors, accessing a second BDD representing health states associated with specified data ranges, and constructing a third BDD by performing an AND operation between the first and second BDDs.

Abstract: One embodiment accesses a binary decision diagram (BDD) representing a function having n variables; constructs one group of one ordered set of the n variables; recursively constructs one or more new groups of one or more ordered sets of one or more variables, replacing existing groups of one or more ordered sets of one or more variables, until each existing group comprises one or more ordered sets of k variables or less, where 1?k<n; for each of the one or more existing groups, determines a locally optimum variable order that yields a smallest size among a plurality of different variable orders of the BDD obtained within the group; and selects from one or more locally optimum variable orders corresponding to the one or more existing groups an optimum variable order of the BDD that yields a smallest size among the one or more existing locally optimum variable orders.

Abstract: One embodiment accesses a binary decision diagram (BDD) representing a function having n variables, where n?2, wherein: the BDD comprises n layers corresponding to the n variables, respectively; and the BDD has a first variable order where each variable i is at layer i for 1?i?n; and reorders the n variables of the BDD according to a second variable order denoted as ?(i), where each variable i is at layer ?(i) for 1?i?n, by iteratively and alternatingly swapping one or more first disjoint pairs of consecutive layers during each odd iteration and swapping one or more second disjoint pairs of consecutive layers during each even iteration, until the second variable order is achieved, wherein during each iteration, two consecutive layers are swapped only if a current order of two variables at the two consecutive layers differs from an order of the two variables specified by the second variable order.

Abstract: In certain embodiments, generating a hierarchy of terms includes accessing a corpus comprising terms. The following is performed for one or more terms to yield parent-child relationships: one or more parent terms of a term are identified according to directional affinity; and one or more parent-child relationships are established from the parent terms and each term. A hierarchical graph is automatically generated from the parent-child relationships.

Abstract: In particular embodiments, a method includes accessing data streams from at least two of an accelerometer, a heart-rate monitor, a blood-pressure monitor, a pulse oximeter, or a mood sensor monitoring a person, analyzing data sets collected from the person when the person is engage and not engaged in a therapy, and determining a current stress factor for the therapy on the person based on the analysis.

Abstract: In particular embodiments, a method includes accessing an original data stream from a sensor, associating a timestamp with each of the samples in the data stream based on a system clock, and recording the original data stream with the associated timestamps.

Abstract: In particular embodiments, a method includes accessing data streams from a first group of physiological sensors monitoring a person, a second group of deconfounding sensors monitoring the person, and a third group of sensors monitoring a stressor, analyzing data sets collected from the person when the person is exposed and not exposed to the stressor, and determining a current stress factor for the stressor with respect to the person based on the analysis.

Abstract: A method for processing access control lists using a hashing scheme includes receiving a packet identifying data and determining a fixed number of a plurality of hash tables comprising a fixed number of two or more buckets comprising a fixed number of one or more entries, such that the two or more hash tables store data in memory associated with an access control list. The method also includes searching the one or more hash tables in parallel for the identifying data using a plurality of hashing functions and returning a search result.