Abstract: A flexible listings search system can receive and return results for flexible listing searches. For example, the system can perform micro-flexible searches (e.g., plus or minus a few days) or super flexible searches (e.g., a time span in one or more months), using listing arrays that can be rapidly accessed to efficiently identify and return results. The search system can further perform flexible destination searches for different categories of accommodations for display in a viewport (e.g., map bounding box). The system can further perform fuzzy searches to identify and return broader results for flexible queries.

Abstract: A search system that receives and returns results for split stays is described. The search system receives, from a searching end-user, a listing request specifying a multiple-day length of stay parameter. The search system determines that the multiple-day length of stay parameter of the listing request transgresses a minimum length of stay threshold and, in response, generates a combined listing that includes a first listing of the plurality of listings associated with a first portion of the multiple-day length of stay parameter and a second listing of the plurality of listings associated with a second portion of the multiple-day length of stay parameter. The combined listing is presented with one or more other listings of the plurality of listings that match the listing request in a ranked order.

Abstract: A flexible listings search system can receive and return results for flexible listing searches. For example, the system can perform micro-flexible searches (e.g., plus or minus a few days) or super flexible searches (e.g., a time span in one or more months), using listing arrays that can be rapidly accessed to efficiently identify and return results. The search system can further perform flexible destination searches for different categories of accommodations for display in a viewport (e.g., map bounding box). The system can further perform fuzzy searches to identify and return broader results for flexible queries.

Abstract: A flexible listings search system can receive and return results for flexible listing searches. For example, the system can perform micro-flexible searches (e.g., plus or minus a few days) or super flexible searches (e.g., a time span in one or more months), using listing arrays that can be rapidly accessed to efficiently identify and return results. The search system can perform flexible destination searches for different categories of accommodations for display in a viewport.

Abstract: Systems and methods are provided for generating a search query based on received user data to perform an internet search using the search query. The systems and methods further extract data from internet search results from the internet search using the search query, generate internet search income records from the extracted data, generate income records from one or more databases comprising income records, and combine the internet search income records and the generated income records from the one or more databases to form combined income record results. The systems and methods further identify candidate income records from the combined income record results, extract features from each candidate income record for generating an income prediction, and generate the income prediction using a machine learning model to predict an income, based on the extracted features from the candidate income records.

Abstract: In one embodiment, a method includes accessing posts of an online social network, each post being associated with a first entity of the online social network, classifying, based on content and metadata associated with each post, one or more of the posts as being relevant to the first entity, extracting a set of one or more n-grams from the content of the posts classified as being relevant to the first entity, filtering the set of n-grams to remove one or more of the extracted n-grams from the set of n-grams, calculating a quality score for each n-gram in the filtered set of n-grams, generating a snippet-module including one or more of the extracted n-grams from the filtered set of n-grams having quality-scores greater than a threshold quality-score, and sending, to a client system of a first user of the online social network, the snippet-module for display to the user.

Abstract: Systems and methods are provided for generating a search query based on received user data to perform an internet search using the search query. The systems and methods further extract data from internet search results from the internet search using the search query, generate internet search income records from the extracted data, generate income records from one or more databases comprising income records, and combine the internet search income records and the generated income records from the one or more databases to form combined income record results. The systems and methods further identify candidate income records from the combined income record results, extract features from each candidate income record for generating an income prediction, and generate the income prediction using a machine learning model to predict an income, based on the extracted features from the candidate income records.

Abstract: In one embodiment, a method includes accessing posts of an online social network, each post being associated with a first entity of the online social network, classifying, based on content and metadata associated with each post, one or more of the posts as being relevant to the first entity, extracting a set of one or more n-grams from the content of the posts classified as being relevant to the first entity, filtering the set of n-grams to remove one or more of the extracted n-grams from the set of n-grams, calculating a quality score for each n-gram in the filtered set of n-grams, generating a snippet-module including one or more of the extracted n-grams from the filtered set of n-grams having quality-scores greater than a threshold quality-score, and sending, to a client system of a first user of the online social network, the snippet-module for display to the user.

Abstract: A classifier development process seamlessly and intelligently integrates different forms of human feedback on instances and features into the data preparation, learning and evaluation stages. A query utility based active learning approach is applicable to different types of editorial feedback. A bi-clustering based technique may be used to further speed up the active learning process.

Abstract: A classifier development process seamlessly and intelligently integrates different forms of human feedback on instances and features into the data preparation, learning and evaluation stages. A query utility based active learning approach is applicable to different types of editorial feedback. A bi-clustering based technique may be used to further speed up the active learning process.