5 research outputs found
Keyphrases analysis of BIM standards through occurrence of most common BIM uses
The 8th PSU-UNS International Conference on Engineering and
Technology (ICET-2017), Novi Sad, Serbia, June 8-10, 2017
University of Novi Sad, Faculty of Technical Sciences
Abstract: Building Information Modeling (BIM) does
not represent only the virtual model of the facility but a
comperhensive approach consisting of technology,
processes, stakeholders' behavior and accompanying
standards.Given the fast evolution of BIM, this paper is
analysing trends of development of BIM standards
throughout the years by applying the keyphrases analysis
method, for some of the most common BIM uses and
recognizable phrases in BIM industry
Detection of Sociolinguistic Features in Digital Social Networks for the Detection of Communities
The emergence of digital social networks has transformed society, social groups, and institutions in terms of the communi cation and expression of their opinions. Determining how language variations allow the detection of communities, together with the relevance of specifc vocabulary (proposed by the National Council of Accreditation of Colombia (Consejo Nacional de AcreditaciΓ³n - CNA) to determine the quality evaluation parameters for universities in Colombia) in digital assemblages could lead to a better understanding of their dynamics and social foundations, thus resulting in better communication policies and intervention where necessary. The approach presented in this paper intends to determine what are the semantic spaces (sociolinguistic features) shared by social groups in digital social networks. It includes fve layers based on Design Science Research, which are integrated with Natural Language Processing techniques (NLP), Computational Linguistics (CL), and
Artifcial Intelligence (AI). The approach is validated through a case study wherein the semantic values of a series of βTwit terβ institutional accounts belonging to Colombian Universities are analyzed in terms of the 12 quality factors established by CNA. In addition, the topics and the sociolect used by diferent actors in the university communities are also analyzed. The current approach allows determining the sociolinguistic features of social groups in digital social networks. Its application allows detecting the words or concepts to which each actor of a social group (university) gives more importance in terms of vocabular
Extracting Food Substitutes From Food Diary via Distributional Similarity
Genetic ancestry admixture of patients infected with Influenza A(H1N1)pdm09 sorted by African ancestry. Each individual ancestry is depicted as a column, whereas color represents the proportion of ancestry estimated for that individual (AfricanΒ =Β blue; EuropeanΒ =Β brown; Native AmericanΒ =Β green). (A) Non-hospitalized patients and (B) Hospitalized patients
Knowledge Extraction and Visualization from Textual Sources Intended for Construction Project Management
Π’ΠΎΠΊΠΎΠΌ ΠΆΠΈΠ²ΠΎΡΠ½ΠΎΠ³ ΡΠΈΠΊΠ»ΡΡΠ° ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΎΠ½ΠΎΠ³ ΠΏΡΠΎΡΠ΅ΠΊΡΠ° ΡΡΠ²Π°ΡΠ° ΡΠ΅ Π²Π΅Π»ΠΈΠΊΠΈ ΠΊΠΎΡΠΏΡΡ Π½Π΅ΡΡΡΡΠΊΡΡΠΈΡΠ°Π½ΠΈΡ
ΠΈ ΠΏΠΎΠ»ΡΡΡΡΡΠΊΡΡΠΈΡΠ°Π½ΠΈΡ
Π΄ΠΎΠΊΡΠΌΠ΅Π½Π°ΡΠ°. Π’ΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π°Π»Π½ΠΈ ΠΏΡΠΈΡΡΡΠΏΠΈ Ρ ΡΠΊΠ»Π°Π΄ΠΈΡΡΠ΅ΡΡ ΠΈ ΠΎΡΠ³Π°Π½ΠΈΠ·ΠΎΠ²Π°ΡΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡΠ° ΠΈΠ· Π½Π΅ΡΡΡΡΠΊΡΡΠΈΡΠ°Π½ΠΈΡ
ΠΏΠΎΠ΄Π°ΡΠΊΠ° ΡΡ ΠΎΡΠΈΡΠ΅Π½ΡΠΈΡΠ°Π½ΠΈ Π½Π° ΡΠ°Π΄ ΡΠ° Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠΈΠΌΠ°, ΡΡΠΎ ΠΈΡ
ΡΠΈΠ½ΠΈ Π½Π΅ΠΏΠΎΠ΄Π΅ΡΠ½ΠΈΠΌ Π·Π° Π°Π½Π°Π»ΠΈΠ·Ρ ΠΈ ΠΈΠ·Π΄Π²Π°ΡΠ°ΡΠ΅ Π·Π½Π°ΡΠ°. Π£ Π½Π΅ΡΡΡΡΠΊΡΡΠΈΡΠ°Π½ΠΈΠΌ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠΈΠΌΠ° ΡΠ΅ ΠΎΡΠ΅ΠΆΠ°Π½ΠΎ ΠΏΡΠΈΠΊΡΠΏΡΠ°ΡΠ΅, Π°Π½Π°Π»ΠΈΠ·Π° ΠΈ ΠΏΠΎΠ½ΠΎΠ²Π½ΠΎ ΠΊΠΎΡΠΈΡΡΠ΅ΡΠ΅ ΡΠ΅Π»Π΅Π²Π°Π½ΡΠ½ΠΈΡ
ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡΠ° Ρ ΠΈΠ½ΡΠ΅Π³ΡΠ°Π»Π½ΠΎΠΌ ΠΎΠ±Π»ΠΈΠΊΡ, ΡΡΠΎ ΠΌΠΎΠΆΠ΅ ΠΈΠ·Π°Π·Π²Π°ΡΠΈ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ΅ Π½Π° ΠΏΡΠΎΡΠ΅ΠΊΡΡ ΡΡΠ»Π΅Π΄ Π½Π΅Π±Π»Π°Π³ΠΎΠ²ΡΠ΅ΠΌΠ΅Π½ΠΈΡ
ΠΈΠ»ΠΈ Π½Π΅ΠΎΠ΄Π³ΠΎΠ²Π°ΡΠ°ΡΡΡΠΈΡ
ΠΎΠ΄Π»ΡΠΊΠ°.
Π£ ΠΎΠ²ΠΎΡ Π΄ΠΈΡΠ΅ΡΡΠ°ΡΠΈΡΠΈ ΡΠ΅ ΠΏΡΠΈΠΊΠ°Π·Π°Π½Π° ΡΠ΅ΠΏΡΠ΅Π·Π΅Π½ΡΠ°ΡΠΈΡΠ° ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡΠ° ΠΈΠ·Π΄Π²ΠΎΡΠ΅Π½ΠΈΡ
ΠΈΠ· Π½Π΅ΡΡΡΡΠΊΡΡΠΈΡΠ°Π½ΠΈΡ
ΡΠ΅ΠΊΡΡΡΠ°Π»Π½ΠΈΡ
Π΄ΠΎΠΊΡΠΌΠ΅Π½Π°ΡΠ° Ρ ΠΎΠ±Π»ΠΈΠΊΡ Π³ΡΠ°ΡΠ° Π·Π½Π°ΡΠ°ΡΠ½ΠΈΡ
ΡΡΠ°Π·Π°, ΠΊΠΎΡΠΈ ΠΊΠΎΡΠΈΡΠ½ΠΈΡΠΈΠΌΠ° ΡΡΠ΅Π±Π° Π΄Π° ΠΎΠΌΠΎΠ³ΡΡΠΈ Π²ΠΈΠ·ΡΠ΅Π»ΠΈΠ·Π°ΡΠΈΡΡ ΠΈ Π°Π½Π°Π»ΠΈΠ·Ρ Π·Π½Π°ΡΠ°ΡΠ½ΠΈΡ
ΡΠΈΡΠ΅Π½ΠΈΡΠ° Π½Π° ΠΏΡΠΎΡΠ΅ΠΊΡΡ ΡΠ° ΠΌΠΈΠ½ΠΈΠΌΠ°Π»Π½ΠΎΠΌ ΠΊΠΎΠ»ΠΈΡΠΈΠ½ΠΎΠΌ ΡΠ»ΠΎΠΆΠ΅Π½ΠΎΠ³ ΡΡΡΠ΄Π°. Π‘Π° ΡΠΈΡΠ΅ΠΌ Π΄Π° ΡΠ΅ ΠΊΠΎΠ½ΡΡΡΡΠΈΡΠ΅ Π΄ΠΎΠΌΠ΅Π½ΡΠΊΠΈ Π½Π΅Π·Π°Π²ΠΈΡΠ½Π° ΡΠ΅ΠΏΡΠ΅Π·Π΅Π½ΡΠ°ΡΠΈΡΠ° ΡΠ° ΠΌΠΈΠ½ΠΈΠΌΠ°Π»Π½ΠΈΠΌ ΡΡΡΠ΄ΠΎΠΌ Π΅ΠΊΡΠΏΠ΅ΡΡΠ° Π·Π° ΠΏΡΠ΅ΡΡ
ΠΎΠ΄Π½ΠΎ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠΈΡΠ°ΡΠ΅, Π·Π½Π°ΡΠ°ΡΠ½Π΅ ΡΡΠ°Π·Π΅ ΡΡ Π΄Π΅ΡΠ΅ΠΊΡΠΎΠ²Π°Π½Π΅ Ρ Π²ΠΈΡΠ΅ΡΠ΅Π·ΠΈΡΠ½ΠΎΠΌ ΠΎΠΊΡΡΠΆΠ΅ΡΡ ΠΏΡΠΈΠΌΠ΅Π½ΠΎΠΌ ΡΡΠ°ΡΠΈΡΡΠΈΡΠΊΠΈΡ
ΠΌΠ΅ΡΠ° Π·Π° ΠΎΠ΄ΡΠ΅ΡΠΈΠ²Π°ΡΠ΅ ΠΊΠΎΡΠ΅Π»ΠΈΡΠ°Π½ΠΎΡΡΠΈ ΠΏΠ°ΡΠ° ΡΠ΅ΡΠΈ. ΠΡΠ°Ρ ΡΠ°Π΄ΡΠΆΠΈ Π°ΡΡΠΎΠΌΠ°ΡΡΠΊΠΈ ΠΈΠ·Π΄Π²ΠΎΡΠ΅Π½Π΅ Π·Π½Π°ΡΠ°ΡΠ½Π΅ ΡΡΠ°Π·Π΅ ΠΊΠΎΡΠ΅ ΡΡ ΠΏΠΎΠ²Π΅Π·Π°Π½Π΅ Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ ΡΠ»ΠΈΡΠ½ΠΎΡΡΠΈ ΡΠ΅ΠΌΠ°Π½ΡΠΈΡΠΊΠΈΡ
ΠΊΠΎΠ½ΡΠ΅ΠΊΡΡΠ°.
Π Π΅ΠΏΡΠ΅Π·Π΅Π½ΡΠ°ΡΠΈΡΠ° ΡΠ΅ ΠΈΠΌΠΏΠ»Π΅ΠΌΠ΅Π½ΡΠΈΡΠ°Π½Π° Ρ Π³ΡΠ°ΡΠΎΠ²ΡΠΊΠΎΡ Π±Π°Π·ΠΈ ΠΏΠΎΠ΄Π°ΡΠ°ΠΊΠ° ΡΡΠΎ ΠΊΠΎΡΠΈΡΠ½ΠΈΡΠΈΠΌΠ° ΠΎΠΌΠΎΠ³ΡΡΠ°Π²Π° Π΄Π° Π΄Π΅ΡΠ΅ΠΊΡΡΡΡ ΠΈ Π²ΠΈΠ·ΡΠ΅Π»ΠΈΠ·ΡΡΡ ΡΠ°Π·Π»ΠΈΡΠΈΡΠ΅ ΡΠΊΡΠΈΠ²Π΅Π½Π΅ ΠΎΠ±ΡΠ°ΡΡΠ΅ Ρ ΠΏΠΎΠ΄Π°ΡΠΈΠΌΠ°. ΠΠ΅ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠ²Π½Π΅ ΡΡΠ°Π·Π΅ ΡΡ ΡΠΈΠ»ΡΡΠΈΡΠ°Π½Π΅ ΠΊΡΠΎΠ· ΠΏΠΎΡΡΡΠΏΠΊΠ΅ ΠΎΠ΄ΡΠ΅ΡΠΈΠ²Π°ΡΠ° Π΅Π½ΡΡΠΎΠΏΠΈΡΠ΅ ΡΠΊΡΠΏΠ° ΠΊΠΎΠ½ΡΠ΅ΠΊΡΡΠ° ΠΈ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ½ΠΎΡΡΠΈ ΡΡΡΠ΅Π΄ΡΡΠ²Π° ΡΡΠ°Π·Π΅ ΠΊΡΠΎΠ· Π²ΠΈΡΠ΅ Π³ΡΠ°ΡΠΎΠ²Π° ΠΊΠΎΡΠΈ ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ°ΡΡ ΡΡΠ΅Π½ΡΡΠΊΠ΅ Ρ Π²ΡΠ΅ΠΌΠ΅Π½Ρ. ΠΡΠΈΠΊΠ°Π·Π°Π½Π° ΡΠ΅ Ρ
Π΅ΡΡΠΈΡΡΠΈΠΊΠ° Π·Π° ΠΈΠ·Π΄Π²Π°ΡΠ°ΡΠ΅ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΈΡ
ΠΊΠΎΠ½ΡΠ΅ΠΏΠ°ΡΠ°, Π·Π°ΡΠ½ΠΎΠ²Π°Π½Π° Π½Π° ΠΈΡΠ΅ΡΠ°ΡΠΈΠ²Π½ΠΎΡ ΠΏΡΠΎΡΠ΅Π΄ΡΡΠΈ Π·Π° Π΄Π΅ΡΠ΅ΠΊΡΠΈΡΡ Π±Π»ΠΈΡΠΊΠΈΡ
ΡΡΠ°Π·Π° ΠΊΠΎΡΠ΅ ΠΏΡΠΈΠΏΠ°Π΄Π°ΡΡ ΠΈΡΡΠΎΠΌ ΡΠ΅ΠΌΠ°Π½ΡΠΈΡΠΊΠΎΠΌ ΠΏΠΎΠ΄Π³ΡΠ°ΡΡ. ΠΠΎΠ³ΡΡΠ½ΠΎΡΡΠΈ ΠΏΡΠΈΠΌΠ΅Π½Π΅ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π΅ ΡΠ΅ΠΏΡΠ΅Π·Π΅Π½ΡΠ°ΡΠΈΡΠ΅ ΡΡ Π΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΠ°Π½Π΅ Π½Π° Π³ΡΠ°ΡΡ ΠΊΠΎΠ½ΡΡΡΡΠΈΡΠ°Π½ΠΎΠΌ Π·Π° ΠΏΠΎΡΡΠΎΡΠ΅ΡΠΈ ΠΊΠΎΡΠΏΡΡ Π΄ΠΎΠΊΡΠΌΠ΅Π½Π°ΡΠ° ΡΠ° ΠΌΠ΅ΡΡΠ½Π°ΡΠΎΠ΄Π½ΠΎΠ³ ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΎΠ½ΠΎΠ³ ΠΏΡΠΎΡΠ΅ΠΊΡΠ°.During a construction project lifecycle, an extensive corpus of unstructured or semi-structured text documents is generated. Traditional approaches for information storing and organizing are document-oriented, which is highly inconvenient for data analysis and knowledge extraction. The nature of unstructured sources impedes usersβ acquisition, analysis, and reuse of relevant information, leading to possible negative effects in the project management process.
This dissertation suggests a procedure for automatic extraction of relevant project concepts from unstructured text documents. Concepts are organized in the form of a key-phrase network, intended to provide users with the possibility to visualize and analyze valuable project facts with less effort. With the objective of constructing a domain-independent and language-independent key-phrase network, with minimal expert involvement for configuration, an approach to detect key phrases was examined by using measures of correlation for word pairs. A network contains key phrases automatically extracted from various types of unstructured documents, with relations based on the similarity of semantic contexts.
The representation was implemented as a graph database, enabling project participants to extract and visualize various patterns in data. The problem of noisy key phrases was reduced by introducing the entropy score for a set of co-occurring contexts and the measure of phrase neighborhood dynamics throughout construction project lifecycle. A heuristic for extraction of complex concepts is presented, based on the iterative procedure for detection of adjacent key phrases belonging to a same semantic subnetwork. Possible applications, such as concept tracking through time or determination of communication patterns between project participants, is demonstrated using a key-phrase network generated for the existing document corpus from an international construction project
Appropriately Incorporating Statistical Significance in PMI
Two recent measures incorporate the notion of statistical significance in basic PMI formulation. In some tasks, we find that the new measures perform worse than the PMI. Our analysis shows that while the basic ideas in incorporating statistical significance in PMI are reasonable, they have been applied slightly inappropriately. By fixing this, we get new measures that improve performance over not just PMI but on other popular co-occurrence measures as well. In fact, the revised measures perform reasonably well compared with more resource intensive non co-occurrence based methods also.