Although we may complain about meetings, they are an essential part of an information worker's work life. Consequently, busy people spend a significant amount of time scheduling meetings. We present Calendar.help, a system that provides fast, efficient scheduling through structured workflows. Users interact with the system via email, delegating their scheduling needs to the system as if it were a human personal assistant. Common scheduling scenarios are broken down using well-defined workflows and completed as a series of microtasks that are automated when possible and executed by a human otherwise. Unusual scenarios fall back to a trained human assistant executing an unstructured macrotask. We describe the iterative approach we used to develop Calendar.help, and share the lessons learned from scheduling thousands of meetings during a year of real-world deployments. Our findings provide insight into how complex information tasks can be broken down into repeatable components that can be executed efficiently to improve productivity.
Scheduling meetings is a difficult task that requires communication, coordination, and negotiation among multiple parties @cite_19 , where each person may have conflicting availabilities, and each may use different, non-interoperable tools @cite_26 . The negotiation is itself complex, as meeting times and locations are resources often governed by intricate constraints and external dependencies @cite_0 . Furthermore, the parties may be geographically dispersed, introducing additional constraints due to time zone differences and the need for communication technologies for remote meetings @cite_33 . This negotiation often needs to occur asynchronously, sometimes requiring several days for the parties to reach consensus @cite_9 @cite_30 . Once a meeting is scheduled, it needs continuous maintenance, as new events often prompt meeting updates and re-schedules.
@cite_30 @cite_26 @cite_33 @cite_9 @cite_0 @cite_19
1486300940 1983818780 2108376501 2154125468
Automating routine organizational tasks, such as meeting scheduling, requires a careful balance between the individual (respecting his or her privacy and personal preferences) and the organization (making efficient use of time and other resources). We argue that meeting scheduling is an inherently distributed process, and that negotiating over meetings can be viewed as a distributed search process. Keeping the process tractable requires introducing heuristics to guide distributed schedulers' decisions about what information to exchange and whether or not to propose the same tentative time for several meetings. While we have intuitions about how such heuristics could affect scheduling performance and efficiency, verifying these intuitions requires a more formal model of the meeting schedule problem and process. We present our preliminary work toward this goal, as well as experimental results that validate some of the predictions of our formal model. We also investigate scheduling in overconstrained situations, namely, scheduling of high priority meetings at short notice, which requires cancellation and rescheduling of previously scheduled meetings. Our model provides a springboard into deeper investigations of important issues in distributed artificial intelligence as well, and we outline our ongoing work in this direction. Scheduling group meetings requires access to participants' calendars, typically located in scattered pockets or desks. Placing participants' calendars on-line and using a rule-based scheduler to find a time slot would alleviate the problem to some extent, but it often is difficult to trust the results, because correct scheduling rules are elusive, varying with the participants and the agenda of a particular meeting. What's needed is a comprehensive scheduling system that summarizes the available information for quick, flexible, and reliable scheduling. We have developed a prototype of a priority-based, graphical scheduling system called Visual Scheduler (VS). A controlled experiment comparing automatic scheduling with VS to manual scheduling demonstrated the former to be faster and less error prone. A field study conducted over six weeks at the UNC-CH Computer Science Department showed VS to be a generally useful system and provided valuable feedback on ways to enhance the functionality of the system to increase its value as a groupwork tool. In particular, users found priority-based time-slots and access to scheduling decision reasoning advantageous. VS has been in use by more than 75 faculty, staff, and graduate students since Fall 1987. Effectively planning a large multi-track conference requires an understanding of the preferences and constraints of organizers, authors, and attendees. Traditionally, the onus of scheduling the program falls on a few dedicated organizers. Resolving conflicts becomes difficult due to the size and complexity of the schedule and the lack of insight into community members' needs and desires. Cobi presents an alternative approach to conference scheduling that engages the entire community in the planning process. Cobi comprises (a) communitysourcing applications that collect preferences, constraints, and affinity data from community members, and (b) a visual scheduling interface that combines communitysourced data and constraint-solving to enable organizers to make informed improvements to the schedule. This paper describes Cobi's scheduling tool and reports on a live deployment for planning CHI 2013, where organizers considered input from 645 authors and resolved 168 scheduling conflicts. Results show the value of integrating community input with an intelligent user interface to solve complex planning tasks. In the interference scheduling problem, one is given a set of n communication requests described by source-destination pairs of nodes from a metric space. The nodes correspond to devices in a wireless network. Each pair must be assigned a power level and a color such that the pairs in each color class can communicate simultaneously at the specified power levels. The feasibility of simultaneous communication within a color class is defined in terms of the Signal to Interference plus Noise Ratio (SINR) that compares the strength of a signal at a receiver to the sum of the strengths of other signals. The objective is to minimize the number of colors as this corresponds to the time needed to schedule all requests. We introduce an instance-based measure of interference, denoted by I, that enables us to improve on previous results for the interference scheduling problem. We prove the upper and lower bounds in terms of I on the number of steps needed for scheduling a set of requests. For general power assignments, we prove a lower bound of @W(I ([email protected])) steps, where @D denotes the aspect ratio of the metric. When restricting to the two-dimensional Euclidean space (as in the previous work) the bound improves to @W(I [email protected]). Alternatively, when restricting to linear power assignments, the lower bound improves even to @W(I). The lower bounds are complemented by an efficient algorithm computing a schedule for linear power assignments using only O(Ilogn) steps. A more sophisticated algorithm computes a schedule using even only O(I+log^2n) steps. For dense instances in the two-dimensional Euclidean space, this gives a constant factor approximation for scheduling under linear power assignments, which shows that the price for using linear (and, hence, energy-efficient) power assignments is bounded by a factor of O([email protected]). In addition, we extend these results for single-hop scheduling to multi-hop scheduling and combined scheduling and routing problems, where our analysis generalizes the previous results towards general metrics and improves on the previous approximation factors.