Abstract: Techniques for creating a user network based on user interest in a product are described. For example, a first search query is received from a first client device. The first client device is associated with a first user. A second search query is received from a second client device. The second client device is associated with a second user. The first search query is matched to a product. The second search query is matched to the product. A user network corresponding to the product is created. The first user is added to the user network based on the matching of the first search query to the product. The second user is added to the user network based on the matching of the second search query to the product.

Abstract: A system includes a content extraction engine comprising at least one processor and configured to receive a content page for a target product including product data for the target product and noise content unrelated to the target product, identify noise content pertaining to data unrelated to the target product, remove noise content from the content page, thereby generating a remainder content page containing target product data usable to enable product comparison between multiple sources.

Abstract: A system includes a content extraction engine comprising at least one processor and configured to receive a content page for a target product including product data for the target product and noise content unrelated to the target product, identify noise content pertaining to data unrelated to the target product, remove noise content from the content page, thereby generating a remainder content page containing target product data usable to enable product comparison between multiple sources.

Abstract: A system includes a content extraction engine comprising at least one processor and configured to receive a content page for a target product including product data for the target product and noise content unrelated to the target product, identify noise content pertaining to data unrelated to the target product, remove noise content from the content page, thereby generating a remainder content page containing target product data usable to enable product comparison between multiple sources.

Abstract: Techniques for creating a user network based on user interest in a product are described. For example, a first search query is received from a first client device. The first client device is associated with a first user. A second search query is received from a second client device. The second client device is associated with a second user. The first search query is matched to a product. The second search query is matched to the product. A user network corresponding to the product is created. The first user is added to the user network based on the matching of the first search query to the product. The second user is added to the user network based on the matching of the second search query to the product.

Abstract: Techniques for creating a user network based on user interest in a product are described. For example, a first search query is received from a first client device. The first client device is associated with a first user. A second search query is received from a second client device. The second client device is associated with a second user. The first search query is matched to a product. The second search query is matched to the product. A user network corresponding to the product is created. The first user is added to the user network based on the matching of the first search query to the product. The second user is added to the user network based on the matching of the second search query to the product.

Abstract: A system includes a content extraction engine comprising at least one processor and configured to receive a content page for a target product including product data for the target product and noise content unrelated to the target product, identify noise content pertaining to data unrelated to the target product, remove noise content from the content page, thereby generating a remainder content page containing target product data usable to enable product comparison between multiple sources.

Abstract: A system includes a content extraction engine comprising at least one processor and configured to receive a content page including first product data for a target product, remove noise content from the content page, thereby generating a remainder content page, compare the remainder content page to a first synonym list to identify the first product data, the first synonym list including a first data field name, and provide the first product data as associated with the first data field name.

Abstract: A system includes a content extraction engine comprising at least one processor and configured to receive a content page including first product data for a target product, remove noise content from the content page, thereby generating a remainder content page, compare the remainder content page to a first synonym list to identify the first product data, the first synonym list including a first data field name, and provide the first product data as associated with the first data field name.

Abstract: Techniques for extracting similar group elements are described. In one embodiment, a received communication is analyzed for repeating patterns in the elements within the communication. An input may be received via a user interface identifying a particular element of the received communication. A system may then identify a particular position within a repeating pattern that is associated with the particular element. Every element within the communication that is in the same position within the repeating pattern may then be identified, stored, or output in a specified or preselected format. Various embodiments may account for multi-page response communications, various pattern recognition techniques, and automated or user-assisted systems.

Abstract: A system includes a content extraction engine comprising at least one processor and configured to receive a content page including first product data for a target product, remove noise content from the content page, thereby generating a remainder content page, compare the remainder content page to a first synonym list to identify the first product data, the first synonym list including a first data field name, and provide the first product data as associated with the first data field name.

Abstract: A tool is provided that allows a user to select a portion of a web page that contains both labels and data values for a set of fields. The tool extracts the labels and the data values. The user can start a data extraction process to query from other pages that are similarly-formatted to the first page and extract data from these other pages. The relationship between the labels and the values can be determined by traversing the domain object model (DOM) of the first page. The tool may be integrated into a custom web browser that includes a user interface (UI) element that can be switched on and off. When the UI element is off, selection of text operates as in a normal web browser. When the UI element is switched on, selection of text operates as described above to facilitate the extraction of data.

Abstract: Techniques for extracting similar group elements are described. In one embodiment, a received communication is analyzed for repeating patterns in the elements within the communication. An input may be received via a user interface identifying a particular element of the received communication. A system may then identify a particular position within a repeating pattern that is associated with the particular element. Every element within the communication that is in the same position within the repeating pattern may then be identified, stored, or output in a specified or preselected format. Various embodiments may account for multi-page response communications, various pattern recognition techniques, and automated or user-assisted systems.

Abstract: Techniques for creating a user network based on user interest in a product are described. For example, a first search query is received from a first client device. The first client device is associated with a first user. A second search query is received from a second client device. The second client device is associated with a second user. The first search query is matched to a product. The second search query is matched to the product. A user network corresponding to the product is created. The first user is added to the user network based on the matching of the first search query to the product. The second user is added to the user network based on the matching of the second search query to the product.