[0001] The present invention relates to electronic documents, and more particularly to a method for visualizing the relationships among, and retrieving one more groups of documents satisfying a user-defined criterion or set of criteria.
[0002] The volume of electronic information in both personal and corporate data stores is increasing rapidly. Examples of such stores include e-mail messages, word-processed and text documents, contact management tools, and calendars. But the precision and usability of knowledge management and search technology has not kept pace. The vast majority of searches performed today are still keyword searches or fielded searches. A keyword search involves entering a list of words, which are likely to be contained within the body of the document for which the user is searching. A fielded search involves locating documents using lexical strings that have been deliberately placed within the document (usually at the top) with the purpose of facilitating document retrieval.
[0003] These data retrieval techniques suffer from two fundamental flaws. Firstly, they often result in either vast numbers of documents being returned, or, if too many keywords or attribute-value pairs are specified and the user specifies that they must all appear in the document, no documents being returned. Secondly, these techniques are able only to retrieve documents that individually meet the search criteria. If two or more related (but distinct) documents meet the search criteria only when considered as a combined unit, these documents will not be retrieved. Examples of this would include the case where the earlier draft of a document contains a keyword, but where this keyword is absent from the later document; or an e-mail message and an entry in an electronic calendar, where the calendar entry might clarify the context of a reference in the e-mail message. There is a clear need for a search technique that returns sets of related documents that are not merely grouped by textual similarity, but also grouped and sequenced according to the social context in which they were created, modified, or quoted.
[0004] This would make it possible to retrieve a very precise set of documents from a large corpus of data. Hitherto, with conventional search tools, this has only been possible by the use of complex search queries, and the results have been restricted to documents that individually meet the search criteria. It is desirable to be able to retrieve a precise set of documents from a large corpus of texts using relatively simple search queries. It would be of further benefit to present said documents in the context of causally related links (for example, a document containing the minutes of a board meeting has a causal link to an email announcing that meeting), even when those other documents do not, individually, satisfy the search criteria. This would relieve the user of the need for prior knowledge (before running the search) of such details as the exact date on which a message was sent, and who sent it. Existing search tools require such prior knowledge, because they do not establish causal links between documents.
[0005] A method of organizing information is disclosed. The method comprises providing a visualization of actor communications in the context of one or more discussion, a discussion including at least one actor and at least one documented communication.
[0006] The present invention is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements and in which:
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[0047] A method and apparatus for visualizing both the electronic paper trails referred to as “discussions” and the statistical anomalies and patterns that are directly computable from these discussions is disclosed. A discussion in this context is a heterogeneous set of causally related communications and events for which either electronic evidence exists, or can be created to reflect. Thus, a discussion provides a means of reviewing a series of related events that occurred over time. One example of generating such discussions from raw communications data is discussed in more detail in copending application Ser. No ______, entitled “A Method and Apparatus for Retrieving Interrelated Sets of Documents”, filed concurrently herewith (hereinafter referred to as ‘An Apparatus for Sociological Data Mining’). The visualizations and user interface tools described in this application greatly facilitate the efficient and effective review and understanding of such chains of events.
[0048] The views described in the following sections provide both graphic visualizations, as well as a means of navigating through the complex chains of communications and events that comprise the data being visualized. These views may be offered to the user in a Model View Controller (MVC) graphical user interface, or via a web-based application.
[0049] The present invention will typically be used in conjunction with a computer network.
[0050] The present invention is for use with digital computers.
[0051] It will be appreciated by those of ordinary skill in the art that any configuration of the system may be used for various purposes according to the particular implementation. The control logic or software implementing the present invention can be stored in main memory
[0052] It will be apparent to those of ordinary skill in the art that the system, method, and process described herein can be implemented as software stored in main memory
[0053] The present invention may also be embodied in a handheld or portable device containing a subset of the computer hardware components described above. For example, the handheld device may be configured to contain only the bus
[0054] It will be appreciated by those of ordinary skill in the art that any configuration of the system may be used for various purposes according to the particular implementation. The control logic or software implementing the present invention can be stored on any machine-readable medium locally or remotely accessible to processor
[0055] Navigation among views is facilitated by the fact that all of the viewable entities have very close relationships to one another, as depicted in
[0056] Hence, for example, in a view depicting discussions, the user can generally click on an image representing an actor to see additional information about this actor, and vice versa.
[0057] More generally the usage of the user interface flows as shown in
[0058] The results may comprise singleton documents
[0059] Views:
[0060] Participant Graphs: graphs that connect the actions of a certain set of participants as related to one or more discussions
[0061] Activity Graphs: comparative or individual graphs that indicate the historical communication or collaboration activity over time among various actors.
[0062] Overview Graphs: diagrams that contain data on one or more discussions, documents, topic discussion, or other aggregate behavior.
[0063] Document Trail Graphs: diagrams that display data tracing the lifecycle of a document or group of documents, including but not limited to such events as document revisions, check-ins and transmissions.
[0064] Money Trail Graphs: diagrams that chart the flow of money, based on information gleaned from a discussion.
[0065] Transcript View Variations: any primarily text-oriented view that lays out a sequence of events and/or communications
[0066] Object Lifecycle Views: views that are focused on the electronic data objects, rather than on the actors.
[0067] Animation: description of different ways that interactive or animated aids or trial art could be generated from any of the above.
[0068] Related Materials include:
[0069] Querying Tools: any view that can serve the purpose of generating a query, including some of the above
[0070] Case Management Application
[0071] Query Language
[0072] Mobile, Voice & Related Applications
[0073] Participant Graphs
[0074] Participant graphs shown in FIGS.
[0075]
[0076]
[0077]
[0078] Participant graphs show the images
[0079] In this view, each items is depicted as a line connecting two or more actors. The color of the line indicates the type of item. Choices include, but are not limited to:
[0080] Email
[0081] Instant Message
[0082] Sending a document (as an attachment in email)
[0083] Phone call (one version with transcript, one without)
[0084] Voicemail (presuming that it had been processed by a speech to text indexer)
[0085] Wire or other funds transfer
[0086] Fax
[0087] Sending/Receipt of FedEx or other electronically trackable package
[0088] Actors
[0089] If an actor has more than one distinct personality (as defined in ‘An Apparatus for Sociological Data Mining’ patent), in some embodiments of the invention, the user has the option to use a different image or graphic for each such personality. If the user opts not to do this, where multiple personalities exist the system Will use the one graphic provided to represent all personalities, but will tint the image with different colors in order to allow the various distinct personalities to be readily identified. The user may globally specify the color scheme to be used in such cases; for example, the primary personality will always be tinted blue.
[0090] The graph is represented as a timeline of events; the resolution can be increased or decreased using zoom in and out controls. In one embodiment, daytime and nighttime hours are indicated by a change in background color; as shown in
[0091] Originating timestamp and timezone
[0092] Originating geographic location
[0093] Wire transfer amount
[0094] Length of phone call or voicemail message
[0095] Subject or title
[0096] Sensitivity level
[0097] Urgency or priority
[0098] Ending timestamp and timezone
[0099] Return of read receipt timestamp
[0100] Alternately, the user may click on the small icon to get only the timestamp details. In one embodiment, right-clicking on this icon provides an immediate chronology of events just before and after the item in question with timestamp information. This is to help clarify which event preceded which, in those cases where the events were almost contemporaneous. The “content” icon can be used to pull up the content of the document involved in the transaction. In one embodiment, there is also optionally a “More info” icon that can be configured to display other types of data that are appropriate. Examples of such data include, but are not limited to: prior user annotations about the transaction, its retrieval history, or the relation of that transaction to a known workflow pattern.
[0101] In one embodiment, actors are shown partially grayed out if their presence in the transaction was likely, but could not be verified solely on the basis of the electronic evidence. One example of this is the case of a meeting entry pulled from an online group calendar which asserts that Joe, Jack, and John will be present at the meeting. Without other supporting evidence, such as meeting minutes indicating that all parties were present, it cannot be definitively asserted that all three men attended the meeting.
[0102] Mousing over an actor icon will bring up a pop-up with the basic information available on that actor. This includes, but is not limited to, the following:
[0103] Full name
[0104] Title
[0105] Organization
[0106] Primary electronic identity
[0107] Electronic identity conducting the transactions whose lines connect to this icon (if different than the primary)
[0108] Clicking on an actor icon brings up a panel with a chronological list
[0109] In one embodiment, the user interface allows the user to add items that were not originally part of the discussion being visualized. This is done through filling out a form panel, shown in
[0110]
[0111] In one embodiment, the view is implemented as a canvas, so the user may drag and drop shapes, lines, and text on it as they please. In one embodiment, such additions are checked for semantic correctness. For one embodiment, added events are indicated by color, patterns, icon, or some other indicator.
[0112] Events of interest are depicted as icons above or below the canvas from which vertical lines extend, cutting across the canvas at the appropriate point in the X axis. These events fall into one or more of the following categories:
[0113] An event belonging to the discussion, but which is not directly a transaction among its actors. For example, a milestone in a workflow process.
[0114] An event extracted from one of the online calendars of the primary actors in the discussion.
[0115] An event entered manually in the UI by the user
[0116] A canned library of icons to represent common concepts like “meeting” may be provided in the UI; the user may elect to add and use their own images as well. The user may also add descriptive text about the event. This text would appear when the user clicks on the icon representing that event.
[0117] In one embodiment of the invention, numerous animation utilities are provided in order to make the visualizations more vivid. Animation can help accentuate the involvement of certain actors of special interest; it can also highlight the accelerating or decelerating pace of the transactions. Types of animation provided in one embodiment of the invention are as follows:
[0118] Rendering the transaction lines and actor icons individually, in the order and timing in which they occurred, according to a condensed timeline appropriate for viewing in generally less than one minute. This emphasizes the lag time (or lack thereof) between contiguous transactions.
[0119] Similarly, but partially graying out, via compositing or other techniques, all transaction lines rather than not rendering them until their appropriate place in the timeline.
[0120] The layout algorithm for the view can be implemented with a number of commonly available graphing libraries. In one embodiment of the invention, a limit of 8 line connections per actor icon is imposed for readability purposes. For one embodiment, should additional connections be necessary in order to represent the underlying data, a second actor icon will be drawn to accommodate the additional lines. Note that while the graph generally follows a left to right timeline, a reply to an email message or IM will show a line going backwards to indicate that the transaction is a reply to a previous transaction, and that these two transactions should be considered part of a single nested transaction.
[0121] However, from an adherence to the timeline perspective, the placement of the two (or more) actor icons involved will be approximately at the start and end time of the nested transaction. If needed, additional actor icons will be rendered to ensure it. Since the purpose of the visualization is to provide an overview of the related transactions in a discussion, exact centering of the actor icons around the relevant line in the X axis is not considered essential. Exact event chronology information can be had from the ancillary panels that are only a single click away. In one embodiment of the invention, transaction lines are represented with directional arrows. In one of these embodiments, a “reply to” can be indicated with a line that has arrows on both ends; if there were N replies, the number N would be rendered near the appropriate arrow.
[0122] Finally, in one embodiment of the invention, the participant graph view can be used modally as a visual querying interface. The user may select a transaction by selecting its objects with a marquis tool, and generate a Query by Example (QBE) query. One example of QBE queries that may be used with this system is defined in ‘An Apparatus for Sociological Data Mining’. The user may also select individual actor icons in order to see all transactions involving all of these actors.
[0123] Other accompanying UI widgets and tools include, but are not limited to, the following. A panning widget
[0124] “Rainbow” View
[0125] To visualize really large volumes of discussions, or individual messages, a different approach to the visualization is necessary.
[0126] The rainbow view uses a color, pattern, or similar distinguishing mechanism which uses the color spectrum to help users to discern small shifts in the communication activity of a very large population of actors. Specifically, this view is used to pinpoint the amount of communication on specific topics. It is accompanied by a graph below which allows the assignation of numerical values to the colors used in the spectrum view. Maximum density is determined by historical values over the same time span and same or comparable population.
[0127] Activity Graphs
[0128] Activity graphs are used to illustrate the amount of communication among a small set of actors over a user-specified period of time. They may optionally be additionally constricted by topic. Actor sets may be specified in any of the following ways:
[0129] Manual specification of particular actors through the user interface.
[0130] Manual specification of one or more actors, with the checkbox enabled to include the “circle of trust.”
[0131] Manual specification of one or more aggregate actors which may then be expanded in the view.
[0132]
[0133] Referring to
[0134] The coloring of the lines is used to indicate one of the following, depending on how the user has configured the user interface:
[0135] Whether the amount of communication to this actor relative to other individual actors during the same period of time is unusually high or low.
[0136] Whether the amount of communication to this actor is high or low relative to what has historically been the case (presuming that comparison data exists.)
[0137] Whether the amount of communication to this actor as a fraction of total communication to other individual actors is high or low compared to what has been true historically.
[0138] Whether the amount of communication is high or low relative to a particular workflow process, or informally, among teams of similar size working on similar projects, either contemporaneously, historically, or both.
[0139] In one embodiment, the color or pattern of the line indicates the frequency of communication, while the thickness of the line indicates the volume of communication. In another embodiment, the thickness of the line indicates the frequency of communication, while the color or pattern of the line indicates the volume of communication.
[0140] The number of communications can be based on any or all of the following, depending on how the user has configured the user interface:
[0141] Email
[0142] Instant Messages (IM)
[0143] Phone calls
[0144] If for some reason, the user has specified an actor who is totally unconnected to the other actors in the display, the icon for that actor will have no lines attached to it.
[0145] The activity graph can be superimposed on an org chart in order to highlight communication flows that appear to differ from the org chart. In this event, actor titles are listed, and additional lines to indicate reporting relationships may be rendered. It can also be used as a visual querying tool; the user may select two or more actors in order to see all of the discussions, or individual communications between them. The user may also click on the line connecting any
[0146] Average depth of communication
[0147] Average interval between successive communications, optionally calculated bi-directionally
[0148] Breakdown of communications by time (for example if the graph spans the period of one year, the communications would be broken down by the month)
[0149] Document types exchanged
[0150] Average length of communication
[0151] Change from immediately previous observation period of same length
[0152] Anomalies
[0153] Ontologies which trap it
[0154] Overview Graphs
[0155]
[0156] The purpose of the overview graph, shown in
[0157] Initiating actor
[0158] Topic
[0159] Document or communication or event type
[0160] The graphic resulting from this is then scaled to the appropriate dimensions and then placed on the chart. Note that an arbitrary number of discussions may be so rendered on this graph; the view simply becomes longer along the Y axis.
[0161] In addition, the user may configure the user interface to color code all communications originated or received by a particular actor of interest. In one embodiment, numerous parallel thumbnails may be created in a dedicated view in order to help the user observe the overlap between different actors of interest.
[0162] As there may be significant time lags between events in some discussions, in some embodiments, a bounding box is used to help indicate that all of the items in question are members of the same discussion. Connecting lines between discussions are used to depict forks in discussions. Similarly to the participant graph, events and other objects may be added to the graph. Zoom controls allow the resolution to be changed; the different visual representations of days, nights, and weekends/holidays may also be used here.
[0163]
[0164] In another embodiment, the discussion names appear to the left of the view, and one discussion occupies all of the real estate in that range of the Y axis.
[0165] For viewing smaller numbers of discussions,
[0166]
[0167] Another variation of this view uses clustering to group whole discussions together, connecting different clusters by the appropriately colored lines, as shown in
[0168] In this view, shapes
[0169] Document Trail Graphs
[0170] Document trail graphs depict the life cycle of one particular document.
[0171] A timeline
[0172] Document trail graphs further show icons allow the user to see more information
[0173] Money Trail Graphs
[0174] The purpose of the money trail graph, shown in
[0175] Any transactions within a discussion that relate to money transfers, whether they are merely documents discussing the transfer, or documents that in themselves constitute the instruments of transfer, are used to build a money trail graph. The graph displays actors
[0176] Transcript View Variations
[0177] The basic transcript view, shown in FIGS.
[0178] A sequence of documents
[0179] In one embodiment of the invention, shown in
[0180] In one embodiment of the invention, shown in
[0181] In one embodiment of the invention, items of different types are displayed with different background colors or patterns
[0182] In one embodiment of the invention, as shown in
[0183] In one embodiment, shown in
[0184] To make it easier for the user to immediately discern the time of day that an event occurred, in one embodiment, a clock icon
[0185] The summary portion
[0186] Optional UI tools include controls to “fast forward” to the next item created or otherwise involving particular actors. This, like the panning widget, which is also used with this view, is especially useful for long discussions which have many participants associated with them.
[0187] In one embodiment, shown in
[0188] An item may have been deleted, yet leave traces behind of its prior existence. A simple example of this is the case in which message B was a reply to message A, but message A itself no longer exists other than what is to be found in the header and content information of message B. There are two subcases of interest related to this:
[0189] The case in which a great deal of information about A—possibly all—can be reconstructed from other sources.
[0190] The case in which only the suspected existence of A can be posited by the system, but virtually no other information is available.
[0191] These two cases differ considerably in their treatment in the user interface, since in the former case, the main consideration of interest is to inform the user that he is seeing reconstructed and/or partial information. For example, in the above example of message A and message B, the header of information of A would be lost, so there would be no way of knowing who had been cc'ed on A. Thus, in a reconstructed version of A in a transcript view, the “cc:” line content would contain a colored block containing question marks, or another representation of the user's choosing. For one embodiment, the item itself has a grayed out background color, and in one embodiment, a broken zig-zag line across it.
[0192] The latter case by definition presumes that there is no content available to display. An example of this would be references in other documents to a document that there is no independent evidence of; for example, a link that no longer resolves. In that instance, the available information is displayed in the appropriate location in the template. In one embodiment, a certainty factor, as shown in box
[0193] In some situations, the question of whether the deletion (or suspected deletion) of the data was either legal in the context of a given matter, or was in compliance with some defined standard of behavior is of interest. One embodiment of a system for making this determination is described in copending application Ser. No. ______, filed concurrently herewith, and entitled “A M
[0194] In the case of the various graph views, suspected deletions are handled similarly:
[0195] Items which were suspiciously deleted will have an icon.
[0196] Items which were partially or largely reconstructed from other forensically available sources are shown with a zig-zag line across them or have a zig-zag line icon above or to the side of them.
[0197] Items whose content could not be reconstructed at all would bear a red question mark icon.
[0198]
[0199] Querying Tools
[0200] In order to help facilitate the iterative querying that is so essential when the user is confronted with an arbitrarily large and unfamiliar corpus of documents, an extensive querying language is provided. For one embodiment, this language reflects the actor orientation of the document analysis engine that is described in ‘An Apparatus for Sociological Data Mining’ patent. Since it is well known that the vast majority of searches contain one or two keywords, and no operators, it is important for the query language for “discussions” to break away from this standard, but ineffective paradigm. This is accomplished by using a sequential structuring of the query information. It is assumed that the majority, but not all, of queries performed with the query language will be one of the following forms, or subsets of the forms described below.
[0201] In
[0202] In
[0203] In
[0204] For one embodiment, the language generally requires that an actor be specified prior to any other terms. In the event that the actor is immaterial to the query, an actor of “anyone” may be specified, or may be automatically inserted by the system. Individual actors can be specified by first name and last name; if only one or the other is provided, the system will look in the recent command history for that user in an attempt to disambiguate it. If nothing suitable is found, the system will try to match the string to both actor first and last names present in the corpus. It will then present a list of appropriate choices, or if there is only choice echo it back to the user for confirmation. An actor's circle of trust can be specified by adding a plus sign “+” after the actor's name. In the case of an aggregate actor, the union of the actors in the different circles of trust is taken. Similarly, an actor group, such as the set of all employees of ACME Corp. could be specified. Similarly, in one embodiment, certain personalities of a given actor (or actors) can be specified.
[0205] Next, the language uses an operator. For one embodiment, if the operator is omitted, it will be interpreted to mean “knew” or “asserted”. There are two main classes of operators, those involving content creation or observation, and those that do not. Operators may be active or passive in nature relative to the actor. For example, modifying a document is active, while getting promoted to a higher position is passive. Content modification operators include, but are not limited to, the following:
[0206] Asserted: There is text attributable to a particular actor that contains the assertion in question.
[0207] Had reason to believe: This has to do with what knowledge the actor had, on the basis of the electronic record, in the face of omissions. For example, if there were 5 versions of a document prior to it being finalized, but a particular actor was only privy to the initial 4, he might not be aware of the existence of the 5
[0208] Knew: The actor actively engaged in discussion about the topic(s) in question.
[0209] Probably Knew: The actor's membership in a particular circle of trust suggests that even absent specific electronic evidence, that the actor probably was aware of a particular thing.
[0210] Saw: The actor in question saw an instance of the content in question. That the actor saw it is established by either their responding to, or commenting on the material. Other evidence of “saw” includes, but is not limited to, any logged access of a document containing this content.
[0211] May Have Seen: There is relevant content that the actor may have seen, but there is no direct evidence that he saw it. For example, the fact that person A sends person B an email cannot reasonably by itself be construed as person B reading this email, at all or in its entirety.
[0212] All of the above also have negations, which may be specified by the use of either “not” or a minus sign. Non-content operators include employee lifecycle events such as Hire, Departure, Transfer, Promotion, and Role Change. Other non-content events include, but are not limited to: Vacation or leave of absence or sick day, Travel event, Wire transfer send or receive, or Phone call, presuming no transcript of the phone call exists.
[0213] “When” may be specified as any of the following:
[0214] Absolute time, using any of the standard date/time formats.
[0215] Time of day (day, night/evening, morning, afternoon, after hours)
[0216] Day of week (or weekday, weekend)
[0217] Holiday or work day or vacation day or one or more specific actors “out of town” as gauged from online calendars and HR system information.
[0218] Note that all time information is implicitly actor-relative. Differences in time zones, national holidays, and even what is considered “after hours” are addressed. Therefore a “when” phrase is interpreted according to what is true for the greatest number of actors specified in the query. If a different behavior than this is desired by the user, she may explicitly bind the “when” term to either an actor or a specific location. For example:
[0219] 1:00 PM in London
[0220] Holiday in France
[0221] Evening for Linda Holmes
[0222] If “when” is not specified, it is presumed to mean:
[0223] The lifespan of the actor specified in the query, if only one actor is specified.
[0224] The interval of time beginning with the earliest lifespan in the actor group specified in the query, and ending with the latest lifespan (or current date/time,) if an actor group were specified.
[0225] The intersection of actor or personality lifespans as specified in the query, if communication among different actors is required by the query
[0226] The “how” may optionally be specified as either a specific device type, such as a Blackberry, or as a category of device, for example a mobile device. The “how” could also be a fax or a voicemail, or a paper letter. In one embodiment, the “how” is identified by its immediately following an unquoted “by” or “via.”
[0227] The “where” may be optionally specified by entering the geographic location of the actor at the time of their participation in the particular transaction. This can be done hierarchically, if a tree of locations is provided. If there is more than one actor specified in the query, the where is modified by actor. In one embodiment, this is specified as <actor name> in <location> or <actor name> at <location>.
[0228] Because of the highly iterative nature of large corpus querying, any of these operators can be iterated on by either reducing or expanding their scope. As described in ‘An Apparatus for Sociological Data Mining’, for one embodiment, the core engine calculates the primary limiting factors in a query. The information is used to indicate to the user which terms are responsible for very substantially reducing or expanding the result set. To facilitate the appropriate use of such iteration, the system can optionally inform the user on which terms could be generalized or specialized one level further for best effect on the results set. In one embodiment, these alternate queries are run automatically on separate threads at the same time as the base query, in order to facilitate an immediate response to a user question, such as a request for “more” or “less.”
[0229] Content or “What” Operators
[0230] Each of the operators below can be used in the context of retrieving discussions or individual communications, or both. These may be used to override the system defaults described previously. For one embodiment, the actual retrieval behavior of these operators is determined by the current relevance scoring mechanism in place. One example of such relevance scoring is described in ‘An Apparatus for Sociological Data Mining’.
[0231] Keyword (an operator
[0232] Phrase (an operator
[0233] Classifier (an operator
[0234] NamedEntity (an operator
[0235] InDiscussionOnly (a document type
[0236] InSingleDocOnly (a document type
[0237] Evidence Operators
[0238] The second group of operators search over metadata collected from each individual communication as well as relationships between documents created during the evidence accrual process while building discussions. These operators return discussions when applied.
[0239] CommunicationType: Returns all discussions containing certain types of communication items, for example email.
[0240] EventType: Returns all discussions that contain an event of a particular kind, such as a board meeting.
[0241] Event: Returns all discussions that contain a particular instance of an event, for example, the board meeting that occurred on Mar. 15, 2001.
[0242] WithItemRelatedToQuery: Will return all discussions containing communications that are a match for a query, regardless of other parameters.
[0243] WithSimilarEvidenceLinks: Will return all discussions with a certain frequency or statistical distribution of evidence links of specific kinds.
[0244] HaveRevisions: Returns those discussions that have more than one version (i.e., have at least one revision due to the subsequent addition of further evidence.)
[0245] PragmaticTag: Returns any discussions containing one or more items with the given pragmatic tag.
[0246] Multi-Discussion Operators
[0247] The third group of operators search over metadata collected from each discussion as well as relationships between discussions. These operators return discussions when applied.
[0248] WithSimilarProperties: return discussions containing a distribution of properties of contained documents. For instance “discussions where most communications sent after hours”.
[0249] WithSimilarActors: discussions containing specified set of actors, actors can be marked as primary, regular, observer or passive participant. For example:
[0250] primary:<joe rudd>.
[0251] WithSameWorkflow: return all discussions that are an instance of the given template. Templates include formal and informal workflows, etc.
[0252] RelatedDiscussions: return discussions related to the given discussions, for example, offspring.
[0253] The fourth group of operators search over inferred sociological relationships between communications in a discussion. In gen