The research aim is to construct a disease-symptom knowledge graph (DSKG) as cause-effect containing relations relation type determined from downloaded documents on medical web-board resources. Each connects disease-name concept node (a causative-concept node) corresponding having group of correlated symptom-concept/effect-concept features common among some concepts. DSKG benefits non-professio...

A knowledge graph is becoming popular due to its ability describe the real world by using a language that can be understood both humans and machines computer technologies. case study construct of porphyry copper deposits presented in this paper. First all, raw text data collected integrated from selected porphyry-skarn Qinzhou Bay – Hangzhou metallogenic belt, South China. Second, text's entiti...

Existing data-centric methods for protein science generally cannot sufficiently capture and leverage biology knowledge, which may be crucial many tasks. To facilitate research in this field, we create ProteinKG65, a knowledge graph science. Using gene ontology Uniprot base as basis, transform integrate various kinds of with aligned descriptions sequences, respectively, to GO terms entities. Pro...

We present two planners, Randward and Lamar, which are respectively built upon the Downward and LAMA planners. The technique developed in these planners is to randomize heuristic construction so that heuristic plateaus are less frequent and the bias introduced by poor, arbitrary nondeterministic choices in heuristic construction is removed. Specifically, we randomize the FF heuristic, naming th...

Durational Action Timed Automata (DATA) is a semantic model for expressing the behavior of real time systems where actions have durations. In this paper, we propose an approach for translating a DATA structure to a corresponding deterministic one. For this purpose, a meta-model of DATA model and a transformation grammar are defined. Programs are written in Python language and implemented under ...

The construction industry has been suffering from delays and cost overruns for decades. Experienced schedulers programs allocate contingencies (both time) based on professional experiences gained knowledge. Such tacit knowledge not captured, stored, shared with inexperienced schedulers. This paper proposes a graph-based automated scheduling (GAS) method to capture, store, reuse the in schedules...