Abstract: One or more computing devices, systems, and/or methods for generating a set of tips for an entity are provided. For example, users may create user generated content describing an entity, such as a user review for a consumer good, a location, an event, etc. Because a user may be unable to read and digest all of the user reviews for the entity, the user may merely read a few user reviews, and thus miss out on useful information. Accordingly, tip templates, indicative of how tips are linguistically/grammatically constructed, are applied to the user reviews to automatically extract a set of tips for the entity (e.g., “make sure to bring a rain jacket”). The set of tips may be filtered to remove undesirable tips, ranked based upon usefulness, and/or diversified to remove redundant tips. In this way, a set of useful tips may be provided to the user.

Abstract: Methods, systems, and media for lot classification are disclosed. In one example, a classification system for identifying lot listings receives a description for a listing in a publication system, identifies a string in the listing, identifies a quantity word or digit in the string, and converts an identified quantity word into digit form. A normalized string is tokenized to produce tokens, the tokenizing of the normalized string including splitting the normalized string into a series of substrings using a sequence of delimiters. For each substring, an additional split is performed by separating any digit from any other adjacent character, unless that character is another digit, and maintaining an internal character order of each split substring to produce a flattened list of tokenized tokens.

Abstract: One or more computing devices, systems, and/or methods for generating a set of tips for an entity are provided. For example, users may create user generated content describing an entity, such as a user review for a consumer good, a location, an event, etc. Because a user may be unable to read and digest all of the user reviews for the entity, the user may merely read a few user reviews, and thus miss out on useful information. Accordingly, tip templates, indicative of how tips are linguistically/grammatically constructed, are applied to the user reviews to automatically extract a set of tips for the entity (e.g., “make sure to bring a rain jacket”). The set of tips may be filtered to remove undesirable tips, ranked based upon usefulness, and/or diversified to remove redundant tips. In this way, a set of useful tips may be provided to the user.

Abstract: A computer implemented method, a computerized system and a computer program product for detecting scalable trends in a personalized search context. The computer implemented method comprising obtaining search results matching a search query, wherein the search query is a query defined by a user, wherein the search results comprise occurrences of events, wherein each occurrence is associated with a timestamp. The method further comprises calculating, by a processor, in response to obtaining the search results, trend scores for the events based on the occurrences comprised by the search results. The method further comprises providing an output to the user based on the trend scores.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content searching, generating, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosure provides a novel, computerized framework for automatically identifying and recommending socially-engaging photos to their creators for sharing. Execution of the disclosed systems and methods turns a tedious manual chore into an automated, software-driven process.

Abstract: One or more computing devices, systems, and/or methods for generating a set of tips for an entity are provided. For example, users may create user generated content describing an entity, such as a user review for a consumer good, a location, an event, etc. Because a user may be unable to read and digest all of the user reviews for the entity, the user may merely read a few user reviews, and thus miss out on useful information. Accordingly, tip templates, indicative of how tips are linguistically/grammatically constructed, are applied to the user reviews to automatically extract a set of tips for the entity (e.g., “make sure to bring a rain jacket”). The set of tips may be filtered to remove undesirable tips, ranked based upon usefulness, and/or diversified to remove redundant tips. In this way, a set of useful tips may be provided to the user.

Abstract: A method, apparatus and computer program product for estimating group expertise, the method comprising: executing a query against a knowledge base to retrieve at least one document; retrieving at least one entity associated with the at least one document; assigning at least one relevancy score to the at least one entity; obtaining a filtered list by filtering the at least one entity to contain only entities appearing in a predetermined collection; and assessing findability of the query based on the at least one entity and the relevancy score.

Abstract: Machines, systems and methods for dynamic content filtering are provided. The method comprises receiving an indication for a preference for an approximate number of content to be delivered during an indicated time period; assigning a first score to the first content according to one or more factors, in response to receiving a first content at a first point in time during the first time period; delivering the first content, in response to determining that the first score is above a first dynamically calculated threshold, wherein the first dynamically calculated threshold is calculated based on: t: time of arrival of the first content, k(t): number of contents that has been delivered until the first point in time, K: the approximate number of events to be delivered during the indicated time period, and F: a distribution function calculated based on prior history of the content delivered.

Abstract: A method and system for highlighting email recipients according to a user's social network are provided. The method includes receiving an email message at a user's email client, the email message having multiple recipients, one of the recipients being the user. The method further includes obtaining a social network list for the user and comparing the social network list for the user with the email message recipients and highlighting recipients in the email message who are also in the social network list. The social network list for a user may be obtained by different methods including using the user's contact resources, or using an aggregating social network system including weighting relationships between contacts.

Abstract: A computer implemented method, a computerized system and a computer program product for detecting scalable trends in a personalized search context. The computer implemented method comprising obtaining search results matching a search query, wherein the search query is a query defined by a user, wherein the search results comprise occurrences of events, wherein each occurrence is associated with a timestamp. The method further comprises calculating, by a processor, in response to obtaining the search results, trend scores for the events based on the occurrences comprised by the search results. The method further comprises providing an output to the user based on the trend scores.

Abstract: A method, apparatus and computer program product for estimating group expertise, the method comprising: executing a query against a knowledge base to retrieve at least one document; retrieving at least one entity associated with the at least one document; assigning at least one relevancy score to the at least one entity; obtaining a filtered list by filtering the at least one entity to contain only entities appearing in a predetermined collection; and assessing findability of the query based on the at least one entity and the relevancy score.

Abstract: Displaying a representative item for a collection of items includes obtaining, from at least one source, a history of interests associated with a user, analyzing the history of interests associated with the user to determine preference criteria for the user, identifying, based on the preference criteria for the user, a representative item for a collection of items, and displaying, to the user, the representative item.

Abstract: Displaying a representative item for a collection of items includes obtaining, from at least one source, a history of interests associated with a user, analyzing the history of interests associated with the user to determine preference criteria for the user, identifying, based on the preference criteria for the user, a representative item for a collection of items, and displaying, to the user, the representative item.

Abstract: An embodiment of the invention provides a method for social network based Wi-Fi, wherein an antenna of a mobile electronic device identifies at least one wireless network within range of the mobile electronic device, and wherein owner(s) of the wireless network(s) are identified with a processor. Relationship status(es) between the owner of the mobile electronic device and the owner(s) of the wireless network(s) are determined with an analysis engine. The wireless network(s) and the relationship status(es) between the owner of the mobile electronic device and the owner(s) of the wireless network(s) are displayed on the mobile electronic device. A request to access a wireless network is received from the owner of the mobile electronic device. Access to the wireless network is automatically granting when the relationship status between the owner of the mobile electronic device and the owner of the wireless network is above a predetermined threshold.

Abstract: An embodiment of the invention provides a method for social network based Wi-Fi, wherein an antenna of a mobile electronic device identifies at least one wireless network within range of the mobile electronic device, and wherein owner(s) of the wireless network(s) are identified with a processor. Relationship status(es) between the owner of the mobile electronic device and the owner(s) of the wireless network(s) are determined with an analysis engine. The wireless network(s) and the relationship status(es) between the owner of the mobile electronic device and the owner(s) of the wireless network(s) are displayed on the mobile electronic device. A request to access a wireless network is received from the owner of the mobile electronic device. Access to the wireless network is automatically granting when the relationship status between the owner of the mobile electronic device and the owner of the wireless network is above a predetermined threshold.

Abstract: Method, system, and computer program product for automatic generation of a word-cloud for a content item are provided. The method includes: extracting terms from a content item using statistical selection criteria; weighting a term by a probability that the term is used as a tag; and generating a visual representation of terms with enhanced representation of terms according to the weighting. Weighting a term by a probability that the term is used as a tag may include determining the relative frequency of the term in a folksonomy of tag terms for a domain.

Abstract: Machines, systems and methods for dynamic content filtering are provided. The method comprises receiving an indication for a preference for an approximate number of content to be delivered during an indicated time period; assigning a first score to the first content according to one or more factors, in response to receiving a first content at a first point in time during the first time period; delivering the first content, in response to determining that the first score is above a first dynamically calculated threshold, wherein the first dynamically calculated threshold is calculated based on: t: time of arrival of the first content, k(t): number of contents that has been delivered until the first point in time, K: the approximate number of events to be delivered during the indicated time period, and F: a distribution function calculated based on prior history of the content delivered.

Abstract: Method, system, and computer program product are provided for scoring of crowd-computing inputs. A group of data is provided to crowd-computing participants and the participants are requested to provide candidate members or the group of data. The computer-implemented method performed includes: receiving an input by a participant, wherein the input is a candidate member; counting multiple inputs of the same candidate member by participants; validating a candidate member; rewarding the participants inputting the candidate member, with a higher reward for participants who input the candidate member earlier than other participants; and supplying the rewards to participants once the candidate member has been validated.

Abstract: A method includes providing data from at least one data source to an analytics engine; outputting data from an identity management system to the analytics engine; outputting data from an enterprise communities database to the analytics engine; causing the analytics engine to issue at least one recommendation based on the data from the at least one data source, the identity management system data and the enterprise communities database data, wherein the determining is executed by at least one processor.

Abstract: A method, system, and computer program product for gap filling in a social network are provided. The method includes providing details of one or more current online users in a game in which users are scored for their input. A person is selected from candidates for whom additional information is required in a social network, including: weighting candidates who have a strong relationship with a current online user in the game; and weighting candidates for whom there is little existing data in the social network. The method includes identifying the selected person to a current online user; receiving information input by a current online user relating to the selected person; and scoring the information input by a current online user.