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<Paper uid="W97-0903">
  <Title>Software Re-Use and Evolution in Text Generation Applications $</Title>
  <Section position="2" start_page="13" end_page="14" type="abstr">
    <SectionTitle>
2 Background
</SectionTitle>
    <Paragraph position="0"> PLANDoc (McKeown et al., 1994), the first major text generation system developed at Bellcore, is an enhancement to Bellcore's LEIS-PLAN TM network planning product. Human engineers use LEIS-PLAN to do network capacity expansion studies, during which they explore alternative scenarios to arrive at an optimal configuration of equipment that meets demands for new services while minimizing costs. PLANDoc produces textual summaries of the scenarios explored by engineers. It transforms lengthy execution traces into human-readable summaries by making heavy use of conjunction, ellipsis, and paraphrasing. It also allows engineers to intersperse their own comments and justifications while using the tool. PLANDoc is currently in widespread use throughout the Southwestern Bell Corporation and has been requested by at least two other regional Bell companies. As an example, Figure 1 shows a fragment of the input to PLANDoc for a particular study, PLANDoc's representation of the same information in canonical form, and the resulting generated sentence.</Paragraph>
    <Paragraph position="1"> FLowDoc (Passonneau et al., 1996) takes as input flow diagrams representing the structure and operations of a business unit, either as it is currently</Paragraph>
    <Paragraph position="3"> (b) PLANDoc's representation of (a) in canonical form.</Paragraph>
    <Paragraph position="4"> RUN-ID FIBERALL demanded that PLAN activate fiber for CSAs 1201, 1301, 1401 and 1501 in 1998 Q2.</Paragraph>
    <Paragraph position="5"> (c) Sentence generated by PLANDoc from the data in (b) and three other similar messages.</Paragraph>
    <Paragraph position="6"> Figure h Sample Input, Canonical Representation, and Output of PLANDoc.</Paragraph>
    <Paragraph position="7"> operating or after a proposed re-organization. Like PLANDoc, it interfaces with another tool developed at Bellcore, SHowBIz, which maintains the  graphical representation and allows the exploration of possible alternatives by the re-engineering consultant. The diagrams resulting from re-engineering analysis are quite complex, with numerous nodes annotated with a large number of attributes. FLOWDOC identifies the core components, participants, and actions of each flow diagram and produces a short textual summary. Figure 2 shows an example input flow diagram, the representation of a sample node in that diagram as presented to FLowDoc by SHOwBIz, FLOWDOC's description of the same in- null : who ' SME : does_what &amp;quot;review&amp;quot; : to_whom_or_what ' dr aft _do cument _in_MS_Wor d_f ormat ) (b) Input representation of a sample node.</Paragraph>
    <Paragraph position="9"> (c) FLowDoc's canonical representation of the information in (b), aggregated with information from two other similar nodes.</Paragraph>
    <Paragraph position="10"> The most frequent tasks in this workflow are those of creating, reviewing aIld saving documents.</Paragraph>
    <Paragraph position="11"> (d) Generated sentence from the canonical message in (c) and from similar messages corresponding to other frequent tasks in the input diagram.  (b) Part of the database output for the query in (a).</Paragraph>
    <Paragraph position="13"> of the information in (b).</Paragraph>
    <Paragraph position="14"> For the ads of interest, the most frequent Internet user domains were European Internet domains at 28 percent and U.8. network domains at 23 percent.  (d) One of the sentences generated by ZEDDoc from the full information about network hosts, which is partially shown in (c).</Paragraph>
    <Paragraph position="15">  sentation, and one of the Corresponding Sentences Produced by ZEDDoc. formation aggregated over several similar nodes in the diagram, and the sentence generated to express this information.</Paragraph>
    <Paragraph position="16"> ZEDDoc summarizes the underlying ZED application's WWW activity. ZED manages a database of advertisement images to satisfy Web advertising contracts. 1 It selects ads to display in predefined slots in a manner that optimizes the satisfaction of the advertising contracts. Whenever ZED displays a Web page, it determines what ads to display and creates database entries for each displayed ad. ZEDDoc integrates a browser, the summary generator, and ZED's Oracle TM database of WWW transactions in a client-server architecture. By accessing the transaction database, ZEDDoc can produce short summaries of ad activity within a user-specified time frame for a user-specified set of ads. Summaries contain, for example, demographic generalizations perl Zed has evolved into a product, the Adapt/X Advertiser TM .</Paragraph>
    <Paragraph position="17"> raining to potentially large numbers of hits. An example of ZEDDoc's input, internal representation, and output is shown in Figure 3.</Paragraph>
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