Search

Large archival collections, such as email or government documents, must be manually reviewed to identify any sensitive information before the collection can be released publicly. Sensitivity classification has received a lot of attention in the literature. However, more recently, there has been increasing interest in developing sensitivity-aware search engines that can provide users with relevant search results, while ensuring that no sensitive documents are returned to the user. Sensitivity-aware search would mitigate the need for a manual sensitivity review prior to collections being made available publicly. To develop such systems, there is a need for test collections that contain relevance assessments for a set of information needs as well as ground-truth labels for a variety of sensitivity categories. The well-known Enron email collection contains a classification ground-truth that can be used to represent sensitive information, e.g., the Purely Personal and Personal but in Professional Context categories can be used to represent sensitive personal information. However, the existing Enron collection does not contain a set of information needs and relevance assessments. In this work, we present a collection of fifty information needs (topics) with crowdsourced query formulations (3 per topic) and relevance assessments (11,471 in total) for the Enron collection (mean number of relevant documents per topic = 11, variance = 34.7). The developed information needs, queries and relevance judgements are available on GitHub and will be available along with the existing Enron collection through the popular ir_datasets library. Our proposed collection results in the first freely available test collection for developing sensitivity-aware search systems.

This document provides lidar-derived elevation data for Napakiak, Southwest Alaska, collected on August 20, 2021. The data includes a classified point cloud, digital surface model (DSM), digital terrain model (DTM), and an intensity model. The survey was conducted to assess flooding hazards and coastal erosion. The data is available for download on the Alaska Division of Geological & Geophysical Surveys website. The document also includes information on the mission plan, processing report, survey report, and acknowledgments. The document provides detailed information on elevation differences at various points, including coordinates and measurements. It also includes information on non-vegetated and vegetated check points, with corrected point cloud elevations and the differences between the corrected point cloud elevations and the checkpoint elevations. The average elevation difference for the non-vegetated check points is -0.007 meters, with a minimum difference of -0.202 meters and a maximum difference of 0.115 meters. The average elevation difference for the vegetated check points is 0.184 meters, with a minimum difference of 0.007 meters and a maximum difference of 0.494 meters. [Extracted from the article]

The article focuses on helping people find military service records, awards, and unit histories with thorough information on how to access various sources, such as personnel files at the National Archives, and ways to receive military awards. Topics include receiving military awards and decorations through the National Personnel Records Center and other pertinent authorities, accessing military service records and pension files, and navigating the corrections process.