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Optimizing execution of top-k queries over record-id ordered, compressed lists is challenging. The threshold family of algorithms cannot be effectively used in such cases. Yet, improving execution of such queries is of great value. For example, top-k keyword search in information retrieval (IR) engines represents an
system (Fexpert) for a research university. Data were undertaken from three sources: (1) researcher's personal profile, (2) graduate school profile and (3) research project profiles. The data were preprocessed and clustered according to each expert's keywords using K-Means algorithm. The proposed system can be used to find
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.