A number of non-overlapping instances of a substring occurring within a string of data elements can be determined through a method that includes partitioning and distributing the string to an ordered list of equal length segments that each have a length greater or equal to L. A substring match within a target segment of the ordered list of segments can be detected by sequentially comparing the substring with each segment of the ordered list of segments. It can be subsequently determined that the target segment contains additional data elements, and a new segment can be generated by clearing L1 data elements following a position of the substring match in the target segment. An additional substring match can be detected by comparing the substring with the new segment.

Disclosed are various embodiments for employing approximate string matching in search queries to locate quotes, such as popular quotes in movies or other media. A quote database may be constructed to respond to search queries that include a quote by identifying approximate matches of the quote in closed captioning files. If an approximate match of a quote resides in the closed captioning file, information associated with the closed captioning file, such as a start time and an end time, may be added to the quote database for use in future searches.

A natural language recognizing apparatus including an input device, a processing device and a storage device is provided. The input device is configured to provide a natural language data. The storage device is configured to store a plurality of program modules. The program modules include a grammar analysis module. The processing device executes the grammar analysis module to analyze the natural language data through a formal grammar model, and generate a plurality of string data. When at least one of the string data conforms to a preset grammar condition, the processing device judges the at least one of the string data is an intention data, and the processing device outputs a corresponding response signal according to the intention data. In addition, a natural language recognizing method is also provided.

Pre-processing before precise pattern matching of a target pattern from a stream of patterns. Including acquiring occurrence numbers of target elements in the target pattern, initializing the buffer, the buffer indicating a section in the stream of patterns, determining whether occurrence numbers of the target elements in the buffer reach the occurrence numbers of the target elements in the target pattern, updating the buffer and then returning to the determining step, in response to determining that the occurrence numbers of the target elements in the buffer do not reach the occurrence numbers of the target elements in the target pattern, and outputting the elements in the buffer for subsequent processing, in response to determining that the occurrence numbers of the target elements in the buffer reach the occurrence numbers of the target elements in the target pattern.

A substring can be detected within a string of data elements through a method that includes partitioning and distributing the string of data elements to an ordered list of segments having equal lengths greater than or equal to the length of the substring. A substring match within a segment of the ordered list of segments can be detected by sequentially comparing the substring with each segment of the ordered list of segments. A carry vector that includes the substring match can be created, in response to detecting the substring match that is a partial match. It can be determined that a carry vector exists by comparing the substring with the segment of the ordered list of segments, and it can be subsequently determined that a full match exists between the carry vector and the segment of the ordered list of segments.

A number of non-overlapping instances of a substring occurring within a string of data elements can be determined through a method that includes partitioning and distributing the string to an ordered list of equal length segments that each have a length greater or equal to L. A substring match within a target segment of the ordered list of segments can be detected by sequentially comparing the substring with each segment of the ordered list of segments. It can be subsequently determined that the target segment contains additional data elements, and a new segment can be generated by clearing L-1 data elements following a position of the substring match in the target segment. An additional substring match can be detected by comparing the substring with the new segment.

Aspects include obtaining a pattern that describes an event in a natural language format. The pattern that describes the event is converted into at least one identified pattern key value pair. A database transaction is monitored and converted into a least one database transaction key value pair. A similarity score is calculated by scoring similarities between the identified pattern key value pair(s) and the database transaction key value pair(s). Based on similarity score meeting a threshold, an alert is output to indicate that the database transaction matches the pattern that describes the event.

Aspects include obtaining a pattern that describes an event in a natural language format. The pattern that describes the event is converted into at least one identified pattern key value pair. A database transaction is monitored and converted into a least one database transaction key value pair. A similarity score is calculated by scoring similarities between the identified pattern key value pair(s) and the database transaction key value pair(s). Based on similarity score meeting a threshold, an alert is output to indicate that the database transaction matches the pattern that describes the event.

A device searches a file being recorded that includes lines sorted in accordance with keys included in the lines to find a line that matches a pattern. When the device receives a pattern, it initializes upper and lower limits of a search range and calculates a middle position between the limits. It acquires, from the file, a middle line that starts at or before the middle position and ends after it. If the key included in the middle line matches the pattern, it outputs the middle line and re-sets the upper or lower limit based on whether the key included in the middle line is greater or less than the pattern and, if there is a distance greater than a length of a newline between the limits, repeats the procedure starting from the middle position. Otherwise, it outputs a result to the effect that no matching line has been found.

Methods, systems, and apparatus for resource locator remarketing are presented. In one aspect, a method includes receiving visitation data from a publisher, the visitation data specifying a device identifier and a resource locator specifying a resource that was provided to a user device; identifying a content feed that includes regular expressions, each regular expression specifying matching character strings and a set of content items that are eligible to be provided to user devices corresponding to visitation data including a resource locator matching one of the regular expressions; identifying, a first matching regular expression that matches the resource locator specified by the visitation data; selecting a content item from the content items that correspond to the first matching regular expression; and providing data that causes presentation of the selected content item to the user device.