SSWP: A Social Semantic Web Portal for Effective Communication in Construction
Bibliographic record
Abstract
Abstract—In the construction industry, there is a pressing need for computer systems that will facilitate information exchange and knowledge sharing among all industry practitioners. The Social Semantic Web Portal (SSWP) proposed in this paper will accomplish three tasks: (1) the streamlining of information exchange about any individual project, (2) the encouragement of knowledge sharing in general, and (3) the virtual grouping of people with similar interests to form communities of practice. A domain ontology is developed in order to encapsulate knowledge about industrial actors and their roles in relation to sibling ontologies that conceptualize construction products and processes. This domain ontology is then tailored to be the cornerstone (the knowledge base) that will enable the semantics of Web services. The concept of the Social Web is employed to validate knowledge items and to connect users with similar interests. The information flow is realized through a content-based publish/subscribe system. The SSWP will semantically connect a user with knowledge items and socially link a user to his/her peers. Index Terms—ontology, information exchange, knowledge
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".