Abstract: A method is disclosed which includes: receiving, from a third-party content provider, a link to a structured document on an external server, where the link is associated with a post of the online social network by the third-party content provider, and retrieving the structured document from the external server, where the structured document includes content and input fields.. This step is followed by extracting a predefined set of information from the structured document about the content and input fields of the structured document. The extracted set of information from the structured document are then evaluated to determine one or more feature-values of the structured document. A machine learning model is used to classify the structured document as an external lead-generation type page based on the one or more feature-values of the structured document and a notification is sent to the third-party content provider if the structured document is classified as an external lead-generation type page.

Abstract: An online system generates a content item for a user based on products likely to be of interest to the user. The online system receives information about content provided by one or more third party systems accessed by the user and determines products associated with accessed content. When the online system identifies an opportunity to present to a user, the online system identifies products for inclusion in the content item and identifies candidate products for inclusion in the content item based on products previously accessed by the user. The online system selects a product of the candidate products based on probabilities of the user accessing content items including different candidate products. The online system includes the content item having information about the selected product in one or more selection processes that select content for presentation to the user.

Abstract: An online system generates a content item for a user based on products likely to be of interest to the user. The online system receives information about products associated one or more third party systems accessed by users of the online system. When the online system identifies an opportunity to present to a user, the online system identifies candidate products for inclusion in the content item based on products previously accessed by the users. For example, the online system identifies candidate products based on products accessed by the user and by one or more other users. The online system may include differing levels of information about a selected candidate product in the content item. In various embodiments, the online system determines a level of information about the selected candidate product based on products previously accessed by the user.

Abstract: In one embodiment, a method includes receiving a set of normalized attribute values that define a particular item being offered and a corresponding threshold score for each of the normalized attribute values. The method further includes, for each attribute value of a candidate item listing, determining a score for the attribute value based on whether it matches a corresponding normalized attribute value, and determining whether the score is above or below the corresponding threshold score for the normalized attribute value. The method still further includes determining whether the candidate item listing describes the particular item being offered based on a set of rules that define an acceptable number of scores that are allowed to be below the threshold scores.

Abstract: In one embodiment, a method includes receiving a plurality of candidate offers that are likely associated with a product being offered for sale. Each candidate offer is associated with a common set of attributes, wherein at least one of the attributes in the common set uniquely identifies the product being offered for sale. The method further includes, for each attribute value of each candidate offer, scoring the attribute value based on an aggregate number of times that the attribute value is found across corresponding attributes of other candidate offers in the plurality, and adding the scores for a first pair of attributes to determine a cumulative score for the candidate offer. One of the attributes in the first pair is the at least one attribute that uniquely identifies the product. The method still further includes updating a set of normalized attribute values for the product to include the attribute values for the first pair of attributes from a highest scoring candidate offer.

Abstract: In one embodiment, a method includes generating a query based on a seed product offer that describes a product being offered for sale and executing the query, using a search engine that normalizes search terms in the query, on a plurality of product offers to determine candidate offers. The candidate offers are likely associated with the product. The method further includes determining one or more common attribute values across corresponding attributes of the candidate offers. The method additionally includes for each attribute value of each candidate offer, scoring the attribute value based on whether it matches one or more of the common attribute values, and updating a set of normalized attribute values for the product to include the attribute value based on whether the score is greater than a predetermined threshold.

Abstract: In one embodiment, a method includes receiving a plurality of uniform resource identifiers (URI's) associated with a particular domain. Each of the URI's identifies a content page comprising one or more signature elements. The method further includes, for each URI in the plurality of URI's, successively testing the URI to identify a core of the URI and any unnecessary elements of the URI. The core of the URI is sufficient to retrieve a version of the content page including all of its signature elements. The method additionally includes, for each URI in the plurality of URI's, updating a set of rules based on the identified core and the identified unnecessary elements. The set of rules establishes a normalized version of the URI.

Abstract: In one embodiment, a method includes extracting a document object model (DOM) for a content page. The DOM comprises a hierarchical tree-based data structure. The method also includes traversing the DOM to identify, in the content page, candidate features of a product page. The method further includes for each of the candidate features, determine candidate feature attributes based on a respective context of the candidate feature in the DOM. The method additionally includes determining whether the content page qualifies as a product page based on whether the candidate features fulfill a required set of characteristics for a product page.

Abstract: In one embodiment, a method includes extracting a document object model (DOM) for a content page, wherein the DOM comprises a hierarchical tree-based data structure. The method also includes identifying candidate nodes in the DOM based on a context of the nodes, wherein the candidate nodes may correspond to listing items. The method additionally includes for each of the candidate nodes, locating its parent and child nodes by traversing the DOM from the candidate node, extracting information from the candidate node and its parent and child nodes, and assessing whether the candidate node qualifies as a listing item based on whether the extracted information fulfills a required set of characteristics for a listing item.

Abstract: Systems and methods for ranking one or more products in online shopping. One or more products are identified based on a search query received from user. The one or more products are ranked based on terms present in the search query. Each of the one or more products has one or more attributes associated with it. An attribute score for each of the one or more products is determined. Further, based on the attribute score, the relevancy of the one or more products is determined. Based on the relevancy, a marginal relevancy score for each of the one or more products is determined. The one or more products are re-ranked based on the marginal relevancy score. The rank of the one or more products can also be modified to optimize revenue generation.

Abstract: Systems and methods for ranking one or more products in online shopping. One or more products are identified based on a search query received from user. The one or more products are ranked based on terms present in the search query. Each of the one or more products has one or more attributes associated with it. An attribute score for each of the one or more products is determined. Further, based on the attribute score, the relevancy of the one or more products is determined. Based on the relevancy, a marginal relevancy score for each of the one or more products is determined. The one or more products are re-ranked based on the marginal relevancy score. The rank of the one or more products can also be modified to optimize revenue generation.

Abstract: Systems and methods for representing and diagnosing interaction sequences in accordance embodiments of the invention are disclosed.

Abstract: Systems and methods for representing and diagnosing interaction sequences in accordance embodiments of the invention are disclosed.

Abstract: A method, system and computer program product for ranking of products related to a product category in online shopping. A search query for one or more products is received from a user. A set of attributes and features of each attribute are extracted related to a product category for each of the one or more products. A score of each attribute is calculated based on the features. Further, the weights are assigned to each of the one or more attributes and a product rank is generated for each of the one or more products based on assigned weights and the score by using a predefined relevancy-ranking algorithm.

Abstract: A method for identifying primary product objects on webpages over the Internet. A primary product object displays the best view of the product that a webpage is detailing. Each webpage is divided into sections based on the primary product objects in the webpage. Features of candidate product objects in each section are extracted. The primary product objects are identified by computing probabilities of the candidate product objects in each section being primary product objects, based on a statistical model. The identified primary product objects are stored for subsequent retrieval and display.

Abstract: The present invention provides a method and a system for identifying relevant information in a data set. The method involves the identification of nodes of interest in a tree structure. A node of interest is a node that contains information, which is relevant to a pre-defined context. The method further involves the step of iteratively extracting sub-trees from the tree structure and identifying records in the extracted sub-trees. The sub-tree is a hierarchical structure that shows the relationship of each node of interest with its ancestor nodes in the tree structure. Each record is a group of sub-tree nodes and contains at least one node of interest.

Abstract: A present invention provides a method and a system for extracting information related to a pre-defined context from data sets written in semi-structured or unstructured form, such as a natural language text. The information related to the pre-defined context is stored in an information store in accordance with a pre-defined structural arrangement. Further, the individual data values in the extracted information are assigned weights depending on their relevance to attributes of the predefined context. The operation of assigning weights to the structured information provides a measure for comparing the relevance of a plurality of structurally arranged information to the attributes of the pre-defined context.

Abstract: The invention provides a method and system to compare data objects. Each data object is converted into a directed acyclic graph forest, which comprises one or more directed acyclic graphs. The directed acyclic graph forests corresponding to data objects are then compared to calculate a similarity score between the data objects. The similarity score is then used as a measure to determine the extent of similarity between the data objects.

Abstract: A method, system and computer program product for ranking of products related to a product category in online shopping. A search query for one or more products is received from a user. A set of attributes and features of each attribute are extracted related to a product category for each of the one or more products. A score of each attribute is calculated based on the features. Further, the weights are assigned to each of the one or more attributes and a product rank is generated for each of the one or more products based on assigned weights and the score by using a predefined relevancy-ranking algorithm.

Abstract: The invention provides a business method and a system to perform focused online shopping and sharing the online shopping experience with other users. The shopping-related information from various sources, and the search query, is converted into directed acyclic graph forests. These graphs are then compared to identify the search results that correspond to the shopping criteria. The sharing of online shopping experience includes sharing of search results between multiple users, discussing the search results through instant messaging (IM), revision of relevant items by any or all users and the flexibility of online-purchase by any user.