Abstract: An online system accesses a two-tower model trained to identify candidate items for presentation to users, in which the model includes an item tower trained to compute item embeddings and a user tower trained to compute user embeddings. The user tower includes a long-term sub-tower trained to compute long-term embeddings for users and a short-term sub-tower trained to compute short-term embeddings for users. The model is trained based on item data associated with items, user data associated with users, and session data associated with user sessions. The system uses the item tower to compute an item embedding for each of multiple candidate items. The system also uses the long-term sub-tower to compute a long-term embedding for a user. The system then receives session data associated with a current session of the user and uses the short-term sub-tower to compute a short-term embedding for the user based on this session data.

Abstract: Content object operations over content objects of a content management system are prioritized to be performed immediately, or at a later time. The immediate scheduling of an operation is determined by policies, rules, and/or predictive model outcomes. The determination for later time scheduling is based on analysis of a history of events on content objects. If the content object operation is deemed to be at least potentially delayable to a later time, then a scheduling model is consulted to determine an urgency of performing the content object operation on the content object. The urgency value resulting from consulting the scheduling model is combined with then-current resource availability to determine a timeframe for performance of the content object operation on the content object relative to other entries in a continuously updated list of to-be-performed operations. The performance of the content object operation on the content object is initiated in due course.

Abstract: Content object operations over content objects of a content management system are prioritized to be performed immediately, or at a later time. The immediate scheduling of an operation is determined by policies, rules, and/or predictive model outcomes. The determination for later time scheduling is based on analysis of a history of events on content objects. If the content object operation is deemed to be at least potentially delayable to a later time, then a scheduling model is consulted to determine an urgency of performing the content object operation on the content object. The urgency value resulting from consulting the scheduling model is combined with then-current resource availability to determine a timeframe for performance of the content object operation on the content object relative to other entries in a continuously updated list of to-be-performed operations. The performance of the content object operation on the content object is initiated in due course.

Abstract: Methods, systems and computer program products for recommendation systems. Embodiments commence by gathering a set of pathnames that refer to content objects of a collaboration system. A tokenizer converts at least some of the pathnames into vectors. The vectors comprise hierarchical path components such as folder names or file names, which vectors are labeled with an indication as to whether or not the folder or file referred to in a particular vector had been clicked on by one or more users. Some portion of the labeled vectors are used to train a predictive model. Another portion of the vectors are used to validate the predictive model. When the model exhibits sufficient precision and recall, the predictive model is then used to predict the probability that a particular user would have an interest in a particular folder or file. The folder name or file name is presented as a collaboration recommendation.

Abstract: Methods, systems and computer program products for computing system security. Techniques for classifying a potentially unauthorized user as an authorized user involve comparisons of two or more access request times that occur at different computing devices in different geographical locations. Based on those comparisons and the distance between the geographical locations of the different computing devices, a determination is made as to whether or not travel (e.g., via overland travel, via air travel, etc.) between those different geographical locations can be reasonably accomplished within a given time period. If it is determined that the required time for travel between the different geographical locations is greater than the time between the access request times—thus suggesting a spoofing attack or other malfeasance—then the potentially unauthorized (i.e.

Abstract: Content object operations over content objects of a content management system are prioritized to be performed immediately, or at a later time. The immediate scheduling of an operation is determined by policies, rules, and/or predictive model outcomes. The determination for later time scheduling is based on analysis of a history of events on content objects. If the content object operation is deemed to be at least potentially delayable to a later time, then a scheduling model is consulted to determine an urgency of performing the content object operation on the content object. The urgency value resulting from consulting the scheduling model is combined with then-current resource availability to determine a timeframe for performance of the content object operation on the content object relative to other entries in a continuously updated list of to-be-performed operations. The performance of the content object operation on the content object is initiated in due course.

Abstract: Methods, systems and computer program products for computing system security. Techniques for classifying a potentially unauthorized user as an authorized user involve comparisons of two or more access request times that occur at different computing devices in different geographical locations. Based on those comparisons and the distance between the geographical locations of the different computing devices, a determination is made as to whether or not travel (e.g., via overland travel, via air travel, etc.) between those different geographical locations can be reasonably accomplished within a given time period. If it is determined that the required time for travel between the different geographical locations is greater than the time between the access request times—thus suggesting a spoofing attack or other malfeasance—then the potentially unauthorized (i.e.

Abstract: A system is provided that generates a list of most common items and respective item frequencies from a data set that includes a plurality of items. The system creates a first list of items from the data set and monitors an estimate count for each item in the first list, where the first list is sorted by the estimate count. The system further transfers items that exceed a threshold hit count from the first list to a second list. The system further monitors a hit count for the items in the second list, where the items in the second list are sorted by the hit count. The system further transfers the items that are displaced from the second list back to the first list.

Abstract: A system performs database management. The system receives a request for a query of a plurality of tables under a join condition on an attribute and determines a uniform mapping that maps a domain of the attribute into a set of numbers, where the domain of the attribute includes all attribute values taken by the attribute in the tables. Then, for a row in a table, the system includes the row into a synopsis of the table if the row includes an attribute value that is mapped by the uniform mapping to a number less than an inclusion probability associated with the table. The system obtains a plurality of synopsis for the tables by repeating the including for all rows in the table and for all tables, and determines, based on the plurality of synopsis, an estimate join size of the tables under the join condition.

Abstract: Techniques are provided for managing cached data objects in a mixed workload environment. In an embodiment, a database system receives request to access a target data object. The database system determines whether the request to access the target data object is associated with a first type of workload or a second type of workload. In response to determining that the request is associated with the first type of workload, the target data object replaces a least recently used data object in a cache. In response to determining that the request is associated with the second type of workload, the target data object is cached based on an associated access-level value.

Abstract: Methods, systems and computer program products for recommendation systems. Embodiments commence by gathering a set of pathnames that refer to content objects of a collaboration system. A tokenizer converts at least some of the pathnames into vectors. The vectors comprise hierarchical path components such as folder names or file names, which vectors are labeled with an indication as to whether or not the folder or file referred to in a particular vector had been clicked on by one or more users. Some portion of the labeled vectors are used to train a predictive model. Another portion of the vectors are used to validate the predictive model. When the model exhibits sufficient precision and recall, the predictive model is then used to predict the probability that a particular user would have an interest in a particular folder or file. The folder name or file name is presented as a collaboration recommendation.

Abstract: A system is provided that generates a list of most common items and respective item frequencies from a data set that includes a plurality of items. The system creates a first list of items from the data set and monitors an estimate count for each item in the first list, where the first list is sorted by the estimate count. The system further transfers items that exceed a threshold hit count from the first list to a second list. The system further monitors a hit count for the items in the second list, where the items in the second list are sorted by the hit count. The system further transfers the items that are displaced from the second list back to the first list.

Abstract: A system performs database management. The system receives a request for a query of a plurality of tables under a join condition on an attribute and determines a uniform mapping that maps a domain of the attribute into a set of numbers, where the domain of the attribute includes all attribute values taken by the attribute in the tables. Then, for a row in a table, the system includes the row into a synopsis of the table if the row includes an attribute value that is mapped by the uniform mapping to a number less than an inclusion probability associated with the table. The system obtains a plurality of synopsis for the tables by repeating the including for all rows in the table and for all tables, and determines, based on the plurality of synopsis, an estimate join size of the tables under the join condition.

Abstract: A system optimizes a number of shared server processes executing on a processor. The system creates, in a memory, a data array for storing a plurality of performance metric values, each associated with a number of shared server processes. The system selects a value for an optimized number of shared server processes according to a first procedure based on the performance metric, observes a performance metric associated with the selected optimized number, and stores, in the data array, the observed performance metric. The system repeats the selecting, observing and storing until at least a predetermined number of contiguous data values are stored in the data array. The system selects the value for the optimized number according to a second procedure based on a slope of the performance metric. The system observes the performance metric associated with the selected optimized number, and stores, in the data array, the observed performance metric.

Abstract: A system optimizes a number of shared server processes executing on a processor. The system creates, in a memory, a data array for storing a plurality of performance metric values, each associated with a number of shared server processes. The system selects a value for an optimized number of shared server processes according to a first procedure based on the performance metric, observes a performance metric associated with the selected optimized number, and stores, in the data array, the observed performance metric. The system repeats the selecting, observing and storing until at least a predetermined number of contiguous data values are stored in the data array. The system selects the value for the optimized number according to a second procedure based on a slope of the performance metric. The system observes the performance metric associated with the selected optimized number, and stores, in the data array, the observed performance metric.

Abstract: A system for optimizing shelf space placement for a product receives decision variables and constraints, and executes a Randomized Search (“RS”) using the decision variables and constraints until an RS solution is below a pre-determined improvement threshold. The system then solves a Mixed-Integer Linear Program (“MILP”) problem using the decision variables and constraints, and using the RS solution as a starting point, to generate a MILP solution. The system repeats the RS executing and MILP solving as long as the MILP solution is not within a predetermined accuracy or does not exceed a predetermined time duration. The system then, based on the final MILP solution, outputs a shelf position and a number of facings for the product.

Abstract: A system is provided that that generates an optimal item placement for one or more items. The system receives one or more items, where each item includes an item height and an item width. The system further receives a container, where the container comprises a container height and a container width. The system further generates a number of copies for each item and a position within the container for each copy of each item, where each copy of each item is placed at the corresponding position within the container. The system further outputs the number of copies for each item and the position within the container for each copy of each item.

Abstract: Techniques are provided for managing cached data objects in a mixed workload environment. In an embodiment, a database system receives request to access a target data object. The database system determines whether the request to access the target data object is associated with a first type of workload or a second type of workload. In response to determining that the request is associated with the first type of workload, the target data object replaces a least recently used data object in a cache. In response to determining that the request is associated with the second type of workload, the target data object is cached based on an associated access-level value.

Abstract: A method for removing cache blocks from a cache queue includes detecting a first cache miss for the cache queue, identifying, within the cache queue, a new cache block storing a value of a storage block, calculating an estimated cache miss cost for a storage container having the storage block, calculating a removal probability for the storage container based on a mathematical formula of the estimated cache miss cost, randomly selecting a probability number from a uniform distribution, where the removal probability exceeds the probability number, and evicting, in response to the removal probability exceeding the probability number, the new cache block from the cache queue.

Abstract: A method of inserting cache blocks into a cache queue includes detecting a first cache miss for the cache queue, identifying a storage block receiving an access in response to the cache miss, calculating a first estimated cache miss cost for a first storage container that includes the storage block, calculating an insertion probability for the first storage container based on a mathematical formula of the first estimated cache miss cost, randomly selecting an insertion probability number from a uniform distribution, and inserting, in response to the insertion probability exceeding the insertion probability number, a new cache block corresponding to the storage block into the cache queue.