
doi: 10.1117/12.962242
A new bidirectional optical associative processor is described for searching a hierarchical database that is stored as an adjacency matrix. The paper discusses how the processor can answer relatively complex queries on a knowledge base when the queries are formulated as combinations of set closures, unions, intersections, and complementations. Thus, a processor that performs general set operations results, as well as a system that can answer various knowledge base queries and guide a knowledge base search. These are new operations for associative processors that increase their utility. This new associative processor operates on entities and their attributes. It can be viewed as a type lattice processor (since the entities and attributes form a hierarchy known as a type lattice), as a closure processor (since it performs closure operations that list all attributes of an entity [or entities] or all entities with a given attribute [or attributes]), or as an adjacency processor (since the connection matrix used stores adjacent associations of attributes and entities).
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
