10.4. Implementing Interactions
The next sections describe some common interactions in digital organizing systems. One way to distinguish among them is to consider the source of the algorithms that are used in order to perform them. We can mostly distinguish information retrieval interactions (e.g., search and browse), machine learning interactions (e.g., cluster, classify, extract) or natural language processing interactions (e.g., named entity recognition, summarization, sentiment analysis, anaphoric resolution). Another way to distinguish among interactions is to note whether resources are changed during the interaction (e.g., annotate, tag, rate, comment) or unchanged (search, cluster). Yet another way would be to distinguish interactions based on their absolute and relative complexity, i.e., on the progression of actions or steps that are needed to complete the interaction. Here, we will distinguish interactions based on the different resource description layers they act upon.
Chapter 3, “Activities in Organizing Systems”, introduced the concept of affordance or behavioral repertoire—the inherent actionable properties that determine what can be done with resources. We will now look at affordances (and constraints) that resource properties pose for interaction design. The interactions that an individual resource can support depend on the nature and extent of its inherent and described properties and internal structure. However, the interactions that can be designed into an organizing ...
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