"... In PAGE 2: ... Relationship analysis helps analysts and designers develop a deeper understanding of the relationship structure of application domains, and provides useful relationships for implementations. Yoo and Bieber (2000) suggest a systematic technique for relationship analysis and also provide a generic, domain-independent relationship taxonomy ( Table1 ) based on an extensive literature review (Yoo 2000). The taxonomy is used to create a set of brainstorming questions that an analyst uses to elicit domain information from the domain expert.... ..."

"... In PAGE 3: ... This is consistent with its name, sitemap-based term propagation model (or ST model in brief). Table2 shows the relationship between the two existing models and the generic framework. Table 2.... In PAGE 3: ...3.3 Two New Propagation Models From Table2 , one can easily think of two new models for relevance propagation (corresponding to the two question marks): hyperlink-based term propagation model (or HT model) and sitemap-based score propagation model (or SS model). Similar to the ST model, the HT model needs to propagate the frequency of query term in a web page before adopting relevance weighting algorithms to rank the documents.... ..."

"... In PAGE 3: ... This is consistent with its name, sitemap-based term propagation model (or ST model in brief). Table2 shows the relationship between the two existing models and the generic framework. Table 2.... In PAGE 3: ...3.3 Two New Propagation Models From Table2 , one can easily think of two new models for relevance propagation (corresponding to the two question marks): hyperlink-based term propagation model (or HT model) and sitemap-based score propagation model (or SS model). Similar to the ST model, the HT model needs to propagate the frequency of query term in a web page before adopting relevance weighting algorithms to rank the documents.... ..."

"... In PAGE 6: ... The fuzzy-neural cooperative model consists of two instances of this basic intelligent stand-alone model, and a protocol is de ned for communication between the managers of the di erent aspects to be optimized. Table1 shows a comparison among the di erent Fuzzy-Neural hybrid models in the literature in relation with the implementation of the tasks carried out by a generic fuzzy system. This generic fuzzy system has been analized using the CommonKADS method- ology in [8] ( gure 4).... ..."

"... In PAGE 7: ... Object versus Agent Design: Basic Concepts 4.2 Modelling Constructs In general, most of the modelling constructs known for objects are useful for agents, too (see Table2 ). We will not go through the list in detail, but state some interesting di erences only: { In general, the agent framework sees all modelling constructs as something which is varying in time and may be modi ed by agents actions.... ..."

"... In PAGE 6: ...ections 3.1.1 and 0. Table1 and Table 2 summarize the indexing structures for the relationships including examples. 3.... In PAGE 6: ... We define spatial and temporal relationships in a special way, however, since we consider the elements as boundaries in space or time with no information about or duration, respectively. See Table1 for a summary of the proposed types of syntactic relationships and examples. Following the work in [5], we divide the spatial relationships into the following classes: (1) topological, i.... In PAGE 6: ...opological, i.e. how boundaries of elements relate; and (2) orientation or directional, i.e. where the elements are placed relative to each other (see Table1 ). Note that these relationships can often be extracted from an audio segment: listening to a stereo broadcast of a news report, for example, it is often easy to assign syntactic attributes to the audio entities.... In PAGE 6: ... Note that the main difference between these relationships and those obtained from visual information lies on the extraction of the relationships themselves- it may be more difficult to determine some spatial relationships from the audio alone, but in creation of synthetic audio models, these relationships play a very important role. In a similar fashion, we classify the temporal relationships into topological and directional classes (see Table1 ). Examples of temporal topological relationships are To happen in parallel , To overlap , and To happen within ; examples of directional temporal relationships are To happen before , and To happen after .... In PAGE 7: ...Audio relationships relate audio entities based on their visual attributes or features. These relationships can be indexed into global, local, and composition classes (see Table1 ). For example, an audio global relationship could be To be less noisy than (based on a global noise feature), an audio local relationship could be is louder than (based on a local loudness measure), and an audio composition relationship could be based on comparing the structures of a Hidden Markov Models.... In PAGE 7: ... For example, an audio global relationship could be To be less noisy than (based on a global noise feature), an audio local relationship could be is louder than (based on a local loudness measure), and an audio composition relationship could be based on comparing the structures of a Hidden Markov Models. In a similar way in which the elements of the audio structure have different levels (generic, specific, and abstract), these types of syntactic relationships (see Table1 ) can be defined in a generic level ( Near ) or a specific level ( 10 meters from ). For example, operational relationships such quot;To be the union of quot;, quot;To be the intersection of quot;, and quot;To be the negation of quot; are topological, specific relationships either spatial or temporal (see Table 1).... ..."