Recording context for conducting searches

Abstract

Procedure, comprehensive: Detect (301), using at least one processor, a user object event, wherein the user object event is selected from a group that includes accessing a user object, saving a user object and transferring a user object, wherein the user object is a file; Collecting (302) using at least one processor, user object event data related to the detected user object event, wherein the user object event data is selected from a group that includes user object creation event data, user object access event data, user object storage event data, user object transfer event data and user object content data; Collect (303), in response to the detection of the user object event and using device sensors located on the first user device and a device in the same location, short-lived data, wherein the short-lived data is selected from a group that includes environmental data, biometric data, light data, audio data, device motion data, device orientation data, location data, hardware connectivity data, device in the same location data, virtual connectivity data, device application data and device state data; Converting (304) the short-lived data into context data, wherein the conversion includes analyzing the short-lived data and forming a searchable context data concept based on the analysis; Generate (305), using at least one processor, an association between the context data and the user object event data; Store (306), in a memory, the association in a data structure accessible to a device application; Accept (401) at an input component of the first user device, a user object search input; Search (405) searchable context data terms of the context data according to the user object search input; Identify (407) a user object using the stored association between the context data and the user object event data; and Output (408) of a search result.

Description

BACKGROUND OF THE INVENTION

[0001] Information processing devices ("Devices"), e.g., laptop computers, tablets, smartphones, CPUs, smart TVs, navigation devices, vehicle consoles, etc., can be used to process search inputs, such as voice or text inputs received when searching for a file, destination, etc. For example, a user enters search term(s), e.g., via keyboard input, spoken input, etc., into an application, which identifies data of interest to the user based on the search term(s). An example of a search is, for example, searching for the user's files, e.g., photos, documents, videos, etc., in a data search application.

[0002] In the publication LEE, Youngseol; CHO, Sung-Bae: “Extracting meaningful contexts from mobile life log”, International Conference on Intelligent Data Engineering and Automated Learning, Springer, Berlin, Heidelberg, 2007, pp. 750-759, a method is described in which log data from smartphones is collected and context data is identified using a KeyGraph method.

[0003] Publication US 2007 / 0 124 292 A1 discloses a wearable device for capturing a comprehensive record of a user's immediate surroundings. All data captured by the device are correlated based on a time reported by a timing device integrated into the wearable device's housing and stored in a memory of the wearable device.

[0004] The publication US 8 020 104 B2 deals with context-related answers based on automated learning methods.

[0005] A search in an index database is known from publication US 7 930 301 B2. Preliminary results are identified that list one or more selected computer objects with selected identification information stored in the index database. Additionally, one or more selected computer objects from the preliminary search results are correlated with one or more other computer objects related to the selected computer objects from the preliminary search results. The returned search results include the preliminary search results and one or more other computer objects related to the selected computer objects from the preliminary search results.

[0006] From the publication EP 2 511 862 A1 an electronic geolocation device is known which comprises a location sensor and a geolocation application which is configured to record location data associated with the device. SHORT DESCRIPTION

[0007] It is an object of the present invention to enable an improved search for a stored file.

[0008] This object is solved by the subject matter of main claim 1 and the independent claims 5 and 6, which determine the present invention.

[0009] Preferred embodiments of the present invention are the subject of the subclaims.

[0010] In summary, one aspect provides a method according to claim 1.

[0011] A further aspect provides an information processing device according to claim 5.

[0012] A further aspect provides a product according to claim 6.

[0013] For a better understanding of the embodiments, together with other and further features and advantages thereof, reference is made to the following description, taken in conjunction with the accompanying drawings. The scope of the invention will be apparent from the appended claims. BRIEF DESCRIPTION OF THE DIFFERENT VIEWS OF THE DRAWINGS Fig. Figure 1 shows an example of a circuit of an information processing device. Fig. Figure 2 shows another example of an information processing device. Fig. Figure 3 illustrates an exemplary method for recording context to perform searches. Fig. Figure 4 illustrates an example method for using context to perform searches. DETAILED DESCRIPTION

[0014] It should be understood that the components of the embodiments, as generally described and illustrated in the figures included herein, may be arranged and configured in a wide variety of different configurations in addition to the described exemplary embodiments. Therefore, the following more detailed description of the exemplary embodiments, as illustrated in the figures, is not limited to the claimed scope of the embodiments, but is merely illustrative of the exemplary embodiments.

[0015] Reference in this specification to "one embodiment" (or the like) means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Therefore, the appearance of the terms "in one embodiment" or the like in various places throughout this specification does not necessarily always refer to the same embodiment.

[0016] Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided in order to provide a thorough understanding of the embodiments. However, those skilled in the art will recognize that the various embodiments may be practiced without one or more of the specific details, or with different methods, components, materials, etc. In other instances, previously known structures, materials, or operations are not shown or described in detail to avoid potential confusion.

[0017] When searching for a file (e.g., a photo, document, music file, etc.), a user tends to remember things based only on the characteristics of the object itself, e.g., title, content, etc., but also based on the context associated with the object. For example, users tend to associate inferred information with events related to the object (e.g., object creation, storage, retrieval, editing, transfer, etc.). This means that users tend to remember what they were doing or what their environment looked like when they last used or interacted with the object. For example, when users search for something, it is often through these alternative associations that users find what they were looking for.

[0018] Current search applications base their searches on the object's characteristics, i.e., the search target. However, it can happen that the object's characteristics (e.g., file name, date / time of storage, etc.) are often unknown to users, are not remembered, or are incorrectly specified by users when entering search terms. In these cases, the search becomes an error-prone and / or tedious endeavor that may not yield relevant results.

[0019] Accordingly, one embodiment collects ephemeral data to provide context information that can be used to expand the search. By recording as much information as possible that can be used to provide or infer the current context, rich and natural associations can be made with user content (referred to herein as “user objects”). It will be further appreciated below that the context data can be derived from a variety of sources, e.g., sensor inputs, information about hardware connections, information about virtual connections, device status information, etc. This collection of data can be described as real-time or ephemeral data, that is, data or information that is currently known but is normally only perceived at a later time. One embodiment uses ephemeral data, for example,via sensors that collect GPS coordinates, audio data, biometric data, device status data, etc. and makes this ephemeral data available to expand the search.

[0020] By recording the ephemeral dataset associated with file, process, application, and / or hardware connection events, it is now possible to rewind to a point in time and reconstruct it to accurately represent the context associated with the object event, e.g., object creation, object access, etc. If this context information is tightly coupled with forensic information, e.g., metadata, keyword extraction, etc., then the associations with the user's context are extremely rich and indeed support low and high correlation orders, which are useful in various search applications. A user could, for example,search for a file based not only on a suspected keyword, but using an embodiment that is also based on where he or she was, when a document was read or edited, or with whom the document was shared during a meeting, or even on the room temperature during retrieval of the document, etc.

[0021] The illustrated exemplary embodiments are better understood with reference to the figures. The following description is for illustrative purposes only and simply presents certain exemplary embodiments.

[0022] Although various other circuit diagrams, circuits or components may be used in the devices with respect to the circuits 10 of smartphones and / or tablets for processing information, a Fig. The example shown in Figure 1 illustrates a system of a single-chip design found, for example, in a tablet or other mobile computing platform. Software and processor(s) are combined in a single chip 110. The processors include internal computing units, registers, cache memories, buses, I / O ports, etc., which are well known in the art. Internal buses and the like depend on the various vendors, but essentially all peripheral devices (120) can be connected to a single chip 110. The circuit 100 includes the processor, memory controller, and I / O control nodes, all in a single chip 110. Systems 100 of this type also typically do not use SATA, PCI, or LPC. Conventional interfaces include SDIO and I2C.

[0023] There are power management chips 130, such as a battery management unit (BMU), that manage power, such as that supplied by a battery 140, which can be recharged by connecting to a power source (not shown). In at least one embodiment, a single chip, such as 110, is used to provide BIOS-like functionality and DRAM memory.

[0024] The system 100 typically includes one or more of a WWAN transceiver 150 and a WLAN transceiver 160 for connecting to various networks, such as telecommunications networks and wireless Internet devices, e.g., access points. Additionally, one of the additional devices 120 is usually a microphone, which may include physical elements that convert sound waves into an electrical audio signal. Typically, the system 100 includes a touchscreen 170 for data entry and display / presentation. The system 100 also typically includes various storage devices, such as flash memory 180 and SDRAM 190.

[0025] Fig. 2 shows a block diagram of another example of circuits, circuit diagrams or components of an information processing device. The Fig. 2 may correspond to computer systems such as the THINKPAD series of personal computers available from Lenovo (US) Inc., in Morrisville, NC, USA, or other devices. As will be apparent from the description contained herein, the embodiments may also include other features or only some of the features shown in the example of Fig. 2 contain the features shown.

[0026] The example of Fig. 2 contains a so-called chipset 210 (a group of integrated circuits, or chips that work together, chipsets) with an architecture that can vary depending on the manufacturer (e.g., INTEL, AMD, ARM, etc.). INTEL is a registered trademark of Intel Corporation in the United States and other countries. AMD is a registered trademark of Advanced Micro Devices, Inc. in the United States and other countries. ARM is not a registered trademark of ARM Holdings plc in the United States and other countries. The architecture of the chipset 210 includes a core and a memory control group 220, as well as an I / O control node 250 that exchanges information (e.g., data, signals, commands, etc.) via a direct management interface (DMI) 242 or an interconnect controller 244. In Fig. 2, the DMI 242 is a chip-to-chip interface (sometimes referred to as a connection between a "northbridge" and a "southbridge"). The core and memory control group 220 includes one or more processors 222 (e.g.,

[0027] Single-core or multi-core) and a memory control node 226 that exchanges information via the front-end bus (FSB) 224. Note that the components of the core and memory control group 220 may be integrated into a single chip, replacing the conventional "northbridge" architecture. One or more processors 220 include internal computing units, registers, cache memories, buses, I / O ports, etc., as are well known in the art.

[0028] In Fig. 2, the memory control node 226 couples to memory 240 (e.g., to provide support for a type of RAM, also referred to as "system memory" or "storage"). The memory control node 226 further includes an LVDS interface 232 for a display device 292 (e.g., a CRT, a flat panel display, a touch screen, etc.). A block 238 includes some technologies that may be supported via the LVDS interface 232 (e.g., serial digital video, HDMI / DVI, display port). The memory control node 226 also includes a PCI Express (PCI-E) interface 234, which may support discrete graphics 236.

[0029] In Fig. 2, the I / O node controller 250 includes a SATA interface 251 (e.g., for HDDs, SDDs, etc., 280), a PCI-E interface 252 (e.g., for wireless connections 282), a USB interface 253 (e.g., for devices 284, such as digital converters, keyboards, mice, cameras, telephones, microphones, storage, other connecting devices, etc.), a network interface 254 (e.g., LAN), a GPIO interface 255, an LPC interface 270 (for ASICs 271, a TPM 272, a Super I / O 273, a firmware node 274, BIOS support 275 as well as various types of memory 276, such as ROM 277, Flash 278, and NVRAM 279), a power management interface 261, a clock interface 262, an audio interface 263 (e.g., for speakers 294), a TCO interface 264, a system management bus interface 265, and an SPI flash 266, which may contain BIOS 268 and boot code 290. The I / O node controller 250 may include Gigabit Ethernet support.

[0030] The system 100, after being powered on, may be configured to execute the boot code 290 for the BIOS 268, as stored within the SPI flash 266, and thus execute data under the control of one or more operating systems and application software (stored, for example, in the system memory 240). An operating system may be stored in any of a variety of locations and accessed according to the instructions of the BIOS 268. As described herein, a device may have fewer or more features than are available in the system of Fig. 2 shown, included.

[0031] Circuits of devices for processing information, such as in Fig. 1 or Fig. 2, can be used in devices that collect short-lived data for use in contextual search, as further described below. Examples of short-lived, real-time data that may be collected, as well as the sensors or other hardware devices or sources included in the collection, include, but are not limited to, environmental data (e.g., temperature, humidity, air pressure, wind speed, wind direction, etc., collected via, e.g., sensors such as thermometers, barometers and / or access to applications containing such information derived from a third party), biometric data (e.g., human presence, human proximity, touch, facial recognition, eye tracking, gaze tracking, etc., e.g., via biometric devices such as fingerprint readers, camera(s) or the like), light data (e.g., ambient, infrared, e.g.,collected via single or multi-dimensional camera(s)), sound data (e.g., a recording derived from microphone(s), etc.), device orientation data (e.g., orientation data collected via a single or multi-dimensional compass, via a single or multi-dimensional inclinometer, etc.), device motion data (e.g., collected via a single or multi-dimensional accelerometer, via a single or multi-dimensional gyrometer, etc.), attitude data (e.g., collected via a global positioning satellite system, via a statistics-collecting system, broadcast and / or dead reckoning data, etc.), measurement data (e.g., triangulation data, barcode data, radio frequency identification (RFID) data, immediate assistance (QR) code data, near-field communication (NFC) data, etc., collected via components configured to collect the same, etc.), time data (e.g., real-time clock data, alarm data, etc.), hardware connection data (e.g. USB connection data, FIREWIRE cable connection data, High Definition Multimedia Interface (HDMI) data, other connection data, etc.), virtual connection data (e.g. open web pages, active RSS feed, received data chains, etc.) and device status data (e.g. open applications, power status, etc.).

[0032] Although such ephemeral data may be collected, for example, using a variety of sensors, it may not be useful until it has been analyzed and converted into another form. GPS data that has not been processed (e.g., analyzed and associated with a landmark) is not particularly useful. Furthermore, such unprocessed data may be in a format unsuitable for use in other applications.

[0033] Therefore, the expression or useful organization of the ephemeral data can be maintained within a data store that has organized data structures, such as context data separators, that contain context data derived from the captured or otherwise obtained ephemeral data, such as an association between GPS data and a known landmark.

[0034] Additionally, the captured or otherwise obtained ephemeral data can be associated with a reference to the user's object(s) (e.g., files, documents, destinations, etc.) such that it is associated with a user object event. GPS or audio data, for example, can be transformed, e.g., analyzed and / or formatted, and then associated, expressed in time and / or location, with a user object event, such as object creation, object editing, object transfer, etc. Therefore, for example, collected ephemeral GPS data can be converted into context data by associating it with a known landmark and then associating it with an object event, e.g., document editing.Similarly, collected ephemeral audio data can be converted into context data by extracting keywords from the audio and associating the keywords with an object event, e.g., emailing the object to a contact on the device.

[0035] Furthermore, these references or associations, e.g., between context data and objects, can be maintained locally (e.g., on the device) and / or in remote storage, e.g., in the cloud. In addition to using file, process, application, and hardware connection events as triggers for collecting ephemeral data, the collection can also occur at regular intervals or otherwise according to a policy. This allows, e.g., the best of the ephemeral data to be shared with devices in the same location and associated with references to the content / user objects of the user's devices. This also allows an extremely busy user device to be less busy and to have the same location. Accordingly, a user device can control its own ephemeral data collection (e.g., throttle) until, e.g.,the particular user device is less busy or otherwise has equivalent processing and / or storage.

[0036] With reference to Fig. 3, therefore, in one embodiment, an object event (e.g., retrieving a user object, saving a user object, transferring a user object, etc.) is captured at 301 and uses this as a trigger to collect object event data at 302. The object event data collected at 302 may include, but is not limited to, a file name of the object, a storage location of the object, a type for the object (e.g., application type), as well as the contents of the object (e.g., keywords).

[0037] Similarly, the object event at 301 triggers a collection of ephemeral data at 303, although the ephemeral data may also be collected without such a trigger, such as according to a time policy. The ephemeral data collected at 303 is associated with the object that is the subject of the object event at 301. Sensor data collected from a plurality of sensors may, for example, be associated with time with the object for which the event occurs, e.g., at 301.

[0038] Given the availability of the ephemeral data collected at 303, an embodiment may convert the ephemeral data into a format usable by the search application, e.g., converting the ephemeral data into context data terms. The ephemeral data is unstructured, and there is currently no conventional way to find personal meaning or context in this ephemeral data.

[0039] A context can consist of ephemeral data captured from a user device, such as sensors, hardware connections, etc. Additionally, information captured from user-generated content / objects, such as keywords, metadata, etc., can be stored by the user device(s) as object event data. Facts captured by current context are combined with user actions, calendar, email, etc., to form correlations or associations.

[0040] As illustrated at 304, the ephemeral data, e.g., GPS data, is analyzed and converted into context data. In this process, the ephemeral data may be converted into keywords or other searchable data. For example, raw ephemeral GPS coordinates may be converted into keywords of nearby locations using map data. Similarly, a sensed user device of the same location, such as a friend or family member's smartphone, may be associated via sensed short-range or near-field wireless communication with a device contact of the user device, which collects the object event data. This information is then collected, converted into a searchable form (e.g., textual form of the location, textual form of the device ID or contact name, etc.), and stored as context data at 304.

[0041] The object event data and context data are associated at 305. In other words, at 305 a reference or connection is created between the context data, i.e. the data derived from the ephemeral data, and the object event data, i.e. the data derived from the event associated with the object. In this way, a store of context data and object event data associated with a particular user object can be created. This store can be used at 306 for use in a variety of applications, such as responding to searches for user objects, as described further herein. This store can be aggregated from different user devices and shared, for example, via cloud account associations, and / or the context data and / or object event data can be stored locally on a single user device. Furthermore, the store can be a distributed store, e.g.For example, context data is stored on one device, object event data on another, and combinations of data can be stored on separate devices for sharing or in similar arrangements. In this sense, a user's devices can be grouped together, for example. Other users can be grouped with a user, who can optionally be enabled in such a group.

[0042] In a user application, e.g., a user object search application, the store of context data and object event data can then be used to provide a more complete picture of the context surrounding the various object events, including the ephemeral data that is easy for the user to remember. Fig. Figure 4 shows an example of using context data in a user object search.

[0043] Therefore, a user may enter a user object search input, such as keywords and / or time limits, etc., into a user object search application at 401. The user object search application may search the user object event data according to the user object search input. In one embodiment, for example, objects may be searched for that have creation times matching the input, that have object types matching the input, that have objects containing keywords matching the input, etc. If the objects are present, as determined at 403, an initial set of search results may be returned at 404. However, if the objects are not so present and / or a set of objects is not so present that the results cannot respond (e.g., due to too many or too few objects), one embodiment may filter the search using the available context data.

[0044] For example, if a user is looking for a document that the user knows was edited at a particular location and within a general time period, searching the object event data may return too many or too many results. Or, if a user correctly remembered the location and time, but not the title, keywords, etc., searching the object event data may not find the correct document or may find too many documents. For example, a search for "find the file I edited last Thursday" may return no results because the user was in meetings all day on Thursday and did not edit any documents. However, the user may have documents that were edited on Tuesday. By expanding the time period, the results may include a result for such a user.

[0045] Accordingly, an embodiment may search the context data at 405, e.g., including location data associated with the document, so that relevant context data, as determined at 406, may be identified. For example, an embodiment may locate a context search term at 406, e.g., a location associated with the user object search input. If so, an embodiment may use the association between that location in the context data store, e.g., in time, with the user object, e.g., the document edited at that location, to return search results that have been filtered (e.g., reordered, ranked differently) or enhanced / modified using the context search. If no relevant context data is found at 406, an embodiment may still return the initial search results based on the object event data.

[0046] It should be noted that the figures shown, such as Fig. 3 and Fig. 4, the steps outlined may be changed or modified. For example, two steps may need to be reversed in their order. Similarly, two steps may be consolidated, or a step may be omitted entirely.

[0047] For example, an embodiment may first attempt to locate the user object that is the subject of the user object search input using the context data. This may be implemented as an adaptive learning process. For example, if a user's search history or profile indicates that the user (or similar users) regularly relies on context data for searching, an embodiment may first employ a search for the context data. Further, if the context data and the object event data are aggregated, the separate searches may be consolidated into a single search. Similarly, an object event data search may occur after the context data search.

[0048] Accordingly, the embodiments described herein may leverage additional context data derived from the ephemeral data in various applications, such as user object search applications. As will be appreciated from the foregoing, this allows a larger amount of data to be used to perform user object searches and allows a user to search using information that is particularly easy to remember, yet conventionally ephemeral, e.g., transient, or otherwise unused.

[0049] Those skilled in the art will appreciate that various aspects may be embodied as a system, method, or device program product.

[0050] Accordingly, some aspects may take the form of an entirely hardware embodiment or an embodiment that includes software, all of which may be generally referred to herein as a "circuit," "module," or "system."

[0051] It should be noted that the various functions described herein may be implemented using instructions stored in a device-readable storage medium, such as a non-signal storage device, executed by a processor. Any combination of one or more device-readable non-signal storage media may be used. A storage medium may be, for example, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof.Even more specific examples of a storage medium would be the following: a portable computer diskette, a hard disk drive, random access memory (RAM), read-only memory (ROM), electronically programmable erasable read-only memory (EPROM or flash memory), an optical fiber, a portable CD-ROM, an optical storage device, a magnetic storage device, or any combination thereof. For the purposes of this document, a storage medium is not a signal and includes "non-transitory" all media except signal media.

[0052] The program code embodied on the storage medium may be transmitted using any suitable medium, including, but not limited to, wireless, wired, optical fiber cable, RF, etc., or any suitable combination thereof.

[0053] The program code for performing operations may be written in any combination of one or more programming languages. The program code may execute entirely on a single device, partially on a single device, as a standalone software package, partially on a single device and partially on another device, or entirely on another device. In some cases, the devices may be connected by any type of connection or network, including a LAN or a WAN, or the connection may be established by other devices (e.g., through the Internet using an Internet service provider), by wireless connections, e.g., near-field communication, or by a wired connection, such as a USB connection.

[0054] Example embodiments are described herein with reference to the figures, which illustrate example methods, devices, and program products according to various example embodiments. It should be understood that the acts and functionality may be implemented, at least in part, by program instructions. These program instructions may be provided to a processor of a general-purpose information processing device, a special-purpose information processing device, or other programmable data processing device to produce a machine, such that the instructions, executing via a processor of the device, implement the specified functions / acts.

[0055] It should be noted that although specific blocks are used in the figures and a particular arrangement of blocks is depicted, these are merely non-limiting examples. In some contexts, two or more blocks may be combined, a block may be divided into two or more blocks, or certain blocks may be rearranged or reorganized at will, as the detailed examples are for illustrative purposes only and are not to be considered limiting.

[0056] As used herein, the singular forms “a” and “an” may include the plural forms “one or more” unless clearly indicated otherwise.

[0057] This disclosure has been presented for purposes of illustration and description, but is by no means intended to be exhaustive or limiting. Many modifications and variations will be readily apparent to those skilled in the art. The exemplary embodiments were chosen and described in order to illustrate the principles and practical applications and to enable the untrained person to understand the disclosure for various embodiments with various modifications as needed for the particular intended use.

[0058] Therefore, although the illustrative, exemplary embodiments have been described with reference to the accompanying figures, it is to be understood that this description is not limiting and that various other changes and modifications may be effected herein by those skilled in the art without departing from the scope or spirit of the disclosure.

Claims

[1] Method comprising: Detecting (301), using at least one processor, a user object event, the user object event being selected from a group comprising accessing a user object, storing a user object, and transferring a user object, the user object being a file; Collecting (302), using at least one processor, user object event data related to the detected user object event, wherein the user object event data is selected from a group comprising user object creation event data, user object access event data, user object storage event data, user object transfer event data, and user object content data; Collecting (303), in response to detecting the user object event and using device sensors located on the first user device and a co-located device, ephemeral data, the ephemeral data being selected from a group comprising environmental data, biometric data, light data, audio data, device motion data, device orientation data, location data, hardware connection data, co-located device data, virtual connection data, device application data, and device status data; Converting (304) the ephemeral data into context data, wherein converting comprises analyzing the ephemeral data and forming a searchable context data term based on the analysis; Creating (305), using at least one processor, an association between the context data and the user object event data; storing (306), in a memory, the association in a data structure accessible to a device application; Accepting (401), at an input component of the first user device, a user object search input; searching (405) searchable context data terms of the context data according to the user object search input; identifying (407) a user object using the stored association between the context data and the user object event data; and Output (408) a search result. [2] The method of claim 1, wherein the storage is selected from the group of storage devices consisting of a local storage device of a first user device, a central storage device accessible to the first user device, and a distributed storage device accessible to the first user device. [3] The method of claim 1, wherein the user object search input contains only searchable context data terms. [4] The method of claim 3, further comprising converting the user object search input into object event data using the association. [5] Device for processing information, comprising: one or more sensors that collect short-lived data; a processor (110); a storage device (180) storing instructions executable by the processor to perform a method according to any one of claims 1 to 4. [6] Product comprising: a storage device having code stored therein, the code comprising code for carrying out a method according to any one of claims 1 to 4.

Images