Abstract: The described techniques relate generally to managing in-person access of users to physical properties based at least in part on tracking geographical locations of devices of the users, such as by using one or more geofences created around a physical property to provide authorized users with temporary access to the physical property based at least in part on tracked geographical locations of devices of the users. In some situations, a specialized server provides information to a user's mobile device about the geofence(s), and the mobile device notifies the specialized server when it breaches one or more of the geofences. The specialized server may perform further related activities, such as perform tracking of locations of users as they move around a physical property, and further analyzing the tracked location information to determine associated information and initiate corresponding additional automated activities.

Abstract: Techniques are described for using computing devices to perform automated operations related to providing visual information of multiple types in an integrated manner about a building or other defined area. The techniques may include generating and presenting a GUI (graphical user interface) on a client device that includes a computer model of the building's interior with one or more first types of information (e.g., in a first pane of the GUI), and simultaneously presenting other types of related information about the building interior (e.g., in additional separate GUI pane(s)) that is coordinated with the first type(s) of information being currently displayed. The computer model may be a 3D (three-dimensional) or 2.5D representation generated after the house is built and showing the actual house's interior (e.g., walls, furniture, etc.), and may be displayed to a user of a client computing device in a displayed GUI with various user-selectable controls.

Abstract: Systems and methods for rearranging tags on a graphical user interface (GUI) based on known and unknown levels of web traffic are disclosed. To provide users with real estate listings that have popular home attributes with respect to a given region, the system uses known user interaction information to determine predicted user interaction information for real estate listing phrases (e.g., tags) that are associated with unknown user interaction information. The system then ranks the real estate listing phrases based on each real estate listing phrase's user interaction information. Based on the ranked real estate listing phrases, the system generates for display the highest ranked real estate listing phrase in association with a real estate listing being associated with the real estate listing phrase.

Abstract: A facility for estimating a value relating to an occurrence is described. The facility receives a first occurrence specifying a first value for each of a plurality of independent variables that include a distinguished independent variable designated to be monotonically linked to a dependent variable. The facility subjects the first independent variable values specified by the received occurrence to a statistical model to obtain a first value of the dependent variable. The facility receives a second occurrence specifying a second value for each of the plurality of independent variables (the second values varying from the first values in a first direction). The facility subjects the second independent variable values to the statistical model to obtain a second value of the dependent variable, the second value of the dependent variable being guaranteed not to vary from the first value of the dependent variable in a second direction opposite the first direction.

Abstract: A facility for estimating a subject home's value is described. For each of one or more direct home attributes, the facility determines the value of the direct home attribute for the subject home. For each of a plurality of arbitrary geographic regions of different sizes containing the subject home, the facility determines information relating to the geographic region as a whole. The facility then subjects the determined values and information to a statistical home valuation model to obtain an estimated value of the subject home.

Abstract: A facility for estimating the value of a distinguished home, estimating the length of time a home or other property will be on the market at a listing price, and predicting the likelihood of sale of a home at a listing price is described.

Abstract: A facility for determining a housing index value for a subject geographic region for a subject period in time is described. For each home in a set of homes within the subject geographic region, the facility determines home attribute values; applies a first valuation model and second valuation for the subject geographic region to the home attributes to obtain estimated values of the home at the beginning and end of the subject period, respectively; and determines an appreciation rate for the home on the basis of the estimated values of the home at the beginning and end of the subject period. The facility combines the appreciation rates to obtain an aggregate appreciation rate for the subject period, and combines the aggregate appreciation rate for the period with a housing index value for a prior period to obtain the housing index value for the subject geographic region and subject period.

Abstract: A system for third party email parsing comprises an input interface and a processor. The input interface is configured to receive an email. The processor is configured to: 1) determine whether the email is from a lead generating system; and 2) in the event that the email is from a lead generating system: a) extract real estate lead information from the email based at least in part on the lead generating system; b) determine whether the real estate lead information is sufficient for a real estate related customer relations management database entry; and c) in the event that the real estate lead information is sufficient for a real estate related customer relations management database entry, add the real estate lead information to a real estate related customer relations management database.

Abstract: Techniques are described for using computing devices to perform automated operations to generate mapping information of a defined area via analysis of visual data of images, including by using attribute information exchanged between paired or otherwise grouped images of multiple types to generate enhanced images, and for using the generated mapping information in further automated manners, including to use the generated mapping information for automated navigation and/or to display or otherwise present the generated mapping information. In some situations, the defined area includes an interior of a multi-room building, and the generated information includes at least one or more enhanced images and/or a partial floor plan and/or other modeled representation of the building, with the generating performed in some cases without having measured depth information about distances from the images' acquisition locations to walls or other objects in the surrounding building.

Abstract: Techniques are described for automated operations related to analyzing visual data from images captured in rooms of a building and optionally additional captured data about the rooms to assess room layout and other usability information for the building's rooms and optionally for the overall building, and to subsequently using the assessed usability information in one or more further automated manners, such as to improve navigation of the building. The automated operations may include identifying one or more objects in each of the rooms to assess and one or more target attributes of each object, and generating and providing instructions to cause the capture of images and optionally additional data about those objects and target attributes for further automated analysis, such as instructions provided to an automated image acquisition device in the room and/or an associated user. Once received, the captured images and other data is then analyzed accordingly.

Abstract: Techniques are described for using computing devices to perform automated operations for determining matching buildings and using corresponding information in further automated manners, such as by determining buildings having similarities to other indicated buildings based at least in part on building floor plans and/or other attributes, and by automatically generating descriptions of the similarities. In some situations, such matching building determinations are based on generating and using adjacency graphs for floor plans that represent inter-connections between rooms and other attributes of the buildings, and further generating and comparing vector-based embeddings that concisely represent the information of the adjacency graphs for use in performing inter-building comparisons and generating the descriptions. Information about such determined buildings may be used in various automated manners, including for controlling device navigation (e.g.

Abstract: Techniques are described for using computing devices to perform automated operations related to, with respect to a computer model of a house or other building's interior, generating and displaying simulated lighting information in the model based on sunlight or other external light that is estimated to enter the building and be visible in particular rooms of the interior under specified conditions, such as using ambient occlusion and light transport matrix calculations. The computer model may be a 3D (three-dimensional) or 2.5D representation that is generated after the house is built and that shows physical components of the actual house's interior (e.g., walls), and may be displayed to a user of a client computing device in a displayed GUI (graphical user interface) via which the user specifies conditions for which the simulated lighting display is generated.

Abstract: Techniques are described for computing devices to perform automated operations related to using images acquired in a building as part of generating a floor plan for the building, in some cases without using depth information from depth-sensing equipment about distances from the images' acquisition locations to objects in the surrounding building, and for subsequent use in further automated manners, such as controlling navigation of mobile devices and/or for display to end users in a corresponding GUI (graphical user interface). In some cases, the MIGM system interacts with an MIGM system operator user, such as by displaying a GUI showing information related to the images and/or a floor plan being generated, and by receiving and using input submitted by the user via the GUI to assist with the generating of the floor plan, such as to specify interconnections between particular rooms via particular inter-room wall openings of the rooms.

Abstract: Techniques are described for automated operations related to analyzing visual data from images captured in rooms of a building and optionally additional captured data about the rooms to assess room layout and other usability information for the building's rooms and optionally for the overall building, and to subsequently using the assessed usability information in one or more further automated manners, such as to improve navigation of the building. The automated operations may include identifying one or more objects in each of the rooms to assess, evaluating one or more target attributes of each object, assessing usability of each object using its target attributes' evaluations and each room using its objects' assessment and other room information with respect to an indicated purpose, and combining the assessments of multiple rooms in a building and other building information to assess usability of the building with respect to its indicated purpose.

Abstract: A valuation system to identify interior features of a property, identify exterior features related to interior features using aerial images, and to generate property valuations based on the identified features is provided. The valuation system identifies, using a computer vision module, interior features based on interior image data (e.g., photos) of a property, and further identifies exterior features associated with any of the interior features based on an aerial photo of the property. For example, trees and buildings (e.g., exterior features) adjacent to a window (e.g., an interior feature) can be identified by a computer vision module through the combination of interior and exterior image data. In other words, the identification of property features by the computer vision module can be enriched by correlating interior image data (e.g., photos, video walkthroughs) to exterior image data (e.g., satellite photos, aerial photos).

Abstract: A facility for valuing a distinguished home located in a distinguished geographic area is described. The facility receives home attributes for the distinguished home. The facility obtains valuation for the distinguished home by applying to the received home attributes evaluation model for homes in the distinguished geographic area that has been trained using selling price and home attribute data from homes recently sold in the distinguished geographic area. The facility reports the obtained valuation for the distinguished home.

Abstract: Estimating a valuation of a target property is disclosed, including receiving user-generated data regarding one or more properties associated with the target property, processing the user-provided data using one or more data models that are configured to process the user-provided data, and combining the output of the one or more data models to obtain an estimated valuation of the target property.

Abstract: A guided search system for suggesting and arranging filter criteria within a user interface for presentation to a user to help guide the user's search for listings is disclosed. The system builds one or more filter criteria frequency data structures indicative of the number of times each filter criterion has been used to filter search results and how often different filter criteria are used together. The system uses the frequency data structures to predict which filter criteria a user will likely employ to narrow their search given the filter criteria the user has already used. The system provides techniques for arranging or rearranging filter criteria within a user interface, by moving, placing, or ordering suggested filter criteria within the user interface, where a user is likely to be able to recognize and interact with the placed filter criteria, based on the determined amounts of use.

Abstract: Techniques are described for using computing devices to perform automated operations related to providing visual information of multiple types in an integrated manner about a building or other defined area. The techniques may include generating and presenting a GUI (graphical user interface) on a client device that includes a computer model of the building's interior with one or more first types of information (e.g., in a first pane of the GUI), and simultaneously presenting other types of related information about the building interior (e.g., in additional separate GUI pane(s)) that is coordinated with the first type(s) of information being currently displayed. The computer model may be a 3D (three-dimensional) or 2.5D representation generated after the house is built and showing the actual house's interior (e.g., walls, furniture, etc.), and may be displayed to a user of a client computing device in a displayed GUI with various user-selectable controls.

Abstract: A specialized server within a real estate showing management system creates a showing appointment for a showing agent to show a listing and a set of geo-fences around the listing when the appointment is created. At a particular time before the showing, the specialized server notifies a showing agent mobile device to download the set of geo-fences and, when requested, provides the set to the mobile device. The mobile device notifies the specialized server when it breaches a geo-fence within the set. The specialized server determines that the showing has started when the notification and the beginning time of the showing appointment are within a predetermined time range. The specialized server then notifies property electronic devices to turn on.