The subject matter described herein relates to search based techniques for initiating tasks within an application.
Conventional user interaction models follow a structured, hierarchical navigation approach. Menus are often provided that group features into certain categories with links that lead to a certain feature. Additionally, buttons can be provided that represent different actions on an object. While such an interaction model presents users with all options that are available, it also requires quite some learning to get familiar with the application. One has to learn which links to follow, where in the menu structure a certain feature is located and which button corresponds to which action, and the like.
As an example, with an application for creating purchase orders, a sample navigation tree might include:
The whole task to create a purchase order with two items involves nine steps, which the user has to memorize. This task implicates the names and positions of various user interface elements such as menu items, hyperlinks, buttons and input fields. Any change in the user interface (e.g., new version of the software, additional features, different vendor, etc.) can disrupt the user's understanding of how the software works, thereby necessitating the user to learn the modified model.
In one aspect, data characterizing one or more terms of a task initiation request within a software application is received. At least one of these terms is associated with a task template. At least a portion of the task template is populated based on the associated one or more terms. Thereafter, the populated task template is presented to enable a user to conduct one or more actions associated with the presented populated task template.
The association of task templates can be based on, for example, polling a data repository (and/or an index of a data repository) to identify one or more stored task templates. Depending on whether there are more than one stored task templates that are associated with the terms, the populated task template can be populated based on two more identified stored task templates. For example, if the search terms are “order pencils”, and the last two orders for pencils were for different amounts, these different amounts may be both displayed to allow the user to select one of them.
The stored task templates can be based on one or more of user-defined rules which map certain terms to certain task templates and historical task templates utilized by the user (and/or entities other than the user).
The populating can comprise a variety of actions that a user would otherwise undertake on a task template. For example, fields of the task template may be populated with values and graphical user interface elements may be activated.
In an interrelated aspect, first data characterizing one or more terms within a task initiation request is received. A data repository is then polled to obtain a plurality of task templates associated with the terms. Second data characterizing the plurality of obtained task templates is presented to a user which results in the receipt of user-generated input selecting one of the presented plurality of obtained task templates. Subsequently, the selected task template is presented to enable the user to conduct one or more actions associated with the presented task template.
In a further interrelated aspect, a system architecture can include a user interface, a parsing engine, a first data repository, an indexing service, an application data store, an execution engine, and a business application. The user interface can receive a user-generated task request containing terms. The parsing engine can parse the task request. The first data repository can be coupled to the parsing engine to store user-defined rules associated search terms with task templates. The indexing service can be coupled to the parsing engine to provide an index characterizing previously generated task templates. The application data store can be coupled to the indexing service to store data characterized in the indexing service. The execution engine can be coupled to the parsing engine to initiate a generation of a task template based on the terms. The business application can be coupled to the execution engine to present a user with a task template in response to a delegation by the execution engine. The business application can also be coupled to the application data store to obtain contextual information based on the terms for at least partially populating the task template.
Articles are also described that comprise a machine-readable medium embodying instructions that when performed by one or more machines result in operations described herein. Similarly, computer systems are also described that may include a processor and a memory coupled to the processor. The memory may encode one or more programs that cause the processor to perform one or more of the operations described herein.
The subject matter described herein provides many advantages. For example, by allowing a user to initiate certain tasks within an application via a key word search rather than by traversing a hierarchical navigation, such tasks may be initiated more rapidly. Moreover, a search-based approach minimizes an amount of time required to complete a task when a traditional hierarchy is modified to reflect new inputs and the like.
The details of one or more variations of the subject matter described herein are set forth in the accompanying drawings and the description below. Other features and advantages of the subject matter described herein will be apparent from the description and drawings, and from the claims.
As used herein, the term task template refers to any interface through which user input is required to complete an action. The task template could be a form, a menu, or workflow approval item, and the like. The term populating as used herein refers to any modification that can occur in relation to a task template including provision of values for certain fields and/or activation of graphical user interface elements on the task template.
In some implementations, the particular task template to be displayed can be based on previous user actions stored in an application data store 360 which have been indexed 350. In other words, the search terms may be associated with previously generated tasks (and their associated task templates). Such previously generated tasks may be grouped in any fashion, such as by user, user workgroup, IP address, and the like. By contextually providing task templates, the amount of time for a user to generate a task can be greatly reduced.
Once the appropriate task template is defined, an execution engine 380 will cause the business application and/or module 390 to initiate the display of the task template (or task templates). As stated above, depending on the contents of the task request, certain aspects of the task template may be pre-populated with values (as described below).
The user interface 320 can include a single input field which allows a user to enter one or more terms. In an example of a purchasing application, the user 310, when seeking to order 4 pencils and 6 notebooks might initiate a task request by entering the following into the input field “order 4 pencils, 6 notebook”. After submitting such a request, a task template 400 as illustrated in
In another example, the user 310 seeks to order the same items but from a specific vendor. In order to access an applicable task template, only the name of the supplier needs to be added to the task request: “order 4 pencils, 6 notebooks, ACME Corp”. The term ACME Corp. formed part of a previous task, and so this company name is included in the indexing service 350 (and the applicable information for ACME Corp. is then obtained from the application data store 380). Therefore, a task template, such as the task template 500 in
As a further example, a few weeks after the most recent order for 4 pencils and 6 notebooks from ACME Corp., the same user 310 submits an abbreviated task request “order pencils”. The indexing service 350 is polled in order to associate this task request with a certain task template. In this scenario, it will be recognized that the user had previously order pencils from ACME Corp. and so a task template populated with the vendor information for ACME Corp. and populated with a value of 4 pencils will be displayed (for the user to subsequently modify or approve) by the business application 370. If a user (or other grouping such as user group, company, IP address, etc.) had previously order pencils either in different amount or from different vendors, then the presented task template may include a drop down list for the value of pencils and for the particular vendor to supply the pencils.
The user interface 320 may also be equipped to simply provide more information regarding users, vendors, and the like. In one example, if the user 310 enters in ACME Corp. without reference to any certain actions, a supplier management module can be invoked so that additional information regarding the vendor can be displayed. Alternatively, the indexing service 350 might cause previously utilized task templates that involved ACME Corp. to be displayed by the business application 370. Similar features can be provided for user name searches. For example, if the entered name is ambiguous, e.g. there are several people named “Smith”, or there is also a supplier company named “Smith”, then the several results will be displayed just like in conventional search. Selection of one of the results will either result in further information being displayed or previously utilized task templates associated with “Smith” being presented.
Additionally features that can be implemented in the task request user interface include, recognition of misspelled or similar terms (“buy” instead of “order”), provision of a history of actions for a particular user (most recent and most used first), auto-completion when typing a content keyword (e.g. a supplier name, etc.), and continuous improvement based on user decisions (e.g. analysis of result clicks etc.).
In some implementations, the searching may relate to a business object or other data object. The following provides a sample search pattern for identifying a relevant object in response to a query.
1. If an object identifier (ID, name, description) is entered without any keywords, show the object details.
2. If the object identifier is ambiguous, present the user with the possible alternatives during the search.
3. If one or more parameter of the task templates is ambiguous (e.g. vendor, no. items for sales order) display a summary of the task, including placeholders for the parameters. The user will then be able to replace the placeholders with actual values.
4. For each placeholder, a list of potential values can be made available. The values with the highest probability (as decided by the system) are placed on top.
In one example, it is desired to view business partner master data. Rather than having to traverse through several sequential windows/menus in order to access master data for a vendor “ACME Associates”, a user can, as illustrated in the window 600 of
In another example, a user desires to create a purchase order. With conventional techniques, a user needs to select a purchase order module, select a vendor (e.g., “ACME Associates”) from a list, select an item to purchase from such vendor, and select a quantity of such items to purchase, all using sequentially presented windows or menus. Using keyword navigation, a user may enter in the terms “order 10 lexmark” into as illustrated in window 800 of
In yet another example, a user desires to display sales of item “A00004” in calendar year 2006. Rather than traversing a plurality of windows, a user can initiate keyword navigation by entering “A00004 sales 2006” into a prompt within a window 1100 as in
Various implementations of the subject matter described herein may be realized in digital electronic circuitry, integrated circuitry, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various implementations may include implementation in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.
These computer programs (also known as programs, software, software applications or code) include machine instructions for a programmable processor, and may be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. As used herein, the term “machine-readable medium” refers to any computer program product, apparatus and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term “machine-readable signal” refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the subject matter described herein may be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user may provide input to the computer. Other kinds of devices may be used to provide for interaction with a user as well; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The subject matter described herein may be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a client computer having a graphical user interface or a Web browser through which a user may interact with an implementation of the subject matter described herein), or any combination of such back-end, middleware, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (“LAN”), a wide area network (“WAN”), and the Internet.
The computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
Although a few variations have been described in detail above, other modifications are possible. For example, the logic flow depicted in the accompanying figures and described herein do not require the particular order shown, or sequential order, to achieve desirable results. In addition, it can be appreciated that the techniques described herein can be used for a wide variety of applications in which a user needs to manually generate some portion of a task. Other embodiments may be within the scope of the following claims.
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