Abstract
In bibliometric research, keyword analysis of publications provides an effective way not only to investigate the knowledge structure of research domains, but also to explore the developing trends within domains. To identify the most representative keywords, many approaches have been proposed. Most of them focus on using statistical regularities, syntax, grammar, or network-based characteristics to select representative keywords for the domain analysis. In this paper, we argue that the domain knowledge is reflected by the semantic meanings behind keywords rather than the keywords themselves. We apply the Google Word2Vec model, a model of a word distribution using deep learning, to represent the semantic meanings of the keywords. Based on this work, we propose a new domain knowledge approach, the Semantic Frequency-Semantic Active Index, similar to Term Frequency-Inverse Document Frequency, to link domain and background information and identify infrequent but important keywords. We adopt a semantic similarity measuring process before statistical computation to compute the frequencies of “semantic units” rather than keyword frequencies. Semantic units are generated by word vector clustering, while the Inverse Document Frequency is extended to include the semantic inverse document frequency; thus only words in the inverse documents with a certain similarity will be counted. Taking geographical natural hazards as the domain and natural hazards as the background discipline, we identify the domain-specific knowledge that distinguishes geographical natural hazards from other types of natural hazards. We compare and discuss the advantages and disadvantages of the proposed method in relation to existing methods, finding that by introducing the semantic meaning of the keywords, our method supports more effective domain knowledge analysis.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (No. 41371372). Thanks Mr. Stephen C. McClure for helping us with the English revisions.
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Appendices
Appendix 1: Top 99 selected keywords from the TF, TF-IDF and TF-KAI methods (the unique keywords are in bold)
Rank | TF | Freq. | TF-IDF | Freq. | TF-KAI | Freq. |
|---|---|---|---|---|---|---|
1 | gis | 94 | gis | 306 | geograph_inform_system_gis | 5,934,569 |
2 | natur_hazard | 64 | geograph_inform_system | 216 | geograph_inform_system | 4,634,698 |
3 | geograph_inform_system | 47 | natur_hazard | 158 | gis | 2,444,443 |
4 | landslid | 43 | geograph_inform_system_gis | 150 | malaysia | 1,139,113 |
5 | vulner | 37 | landslid | 130 | spatial_analysi | 999,469.3 |
6 | geograph_inform_system_gis | 27 | remot_sens | 109 | prison | 979,072 |
7 | Hazard | 26 | vulner | 107 | disast_risk_assess | 925,529 |
8 | remot_sens | 26 | natur_disast | 83 | geograph_variat | 925,529 |
9 | flood | 22 | risk_assess | 67 | frequenc_ratio | 920,429.7 |
10 | natur_disast | 22 | flood | 60 | remot_sens | 790,241.5 |
11 | risk | 22 | earthquak | 51 | urban_geolog | 697,015.1 |
12 | risk_assess | 20 | landslid_suscept | 51 | analyt_hierarchi_process_ahp | 674,641.8 |
13 | disast | 18 | social_vulner | 49 | coastal_vulner_index | 674,641.8 |
14 | earthquak | 16 | disast | 46 | gis_model | 674,641.8 |
15 | climat_chang | 13 | climat_chang | 45 | Pca | 674,641.8 |
16 | resili | 11 | malaysia | 44 | activ_learn | 573,675 |
17 | landslid_suscept | 10 | resili | 40 | anthropogen_intervent | 573,675 |
18 | social_vulner | 10 | bangladesh | 39 | catastroph_theori | 573,675 |
19 | drought | 9 | risk | 39 | climat_variat | 573,675 |
20 | risk_manag | 9 | drought | 38 | cross_applic | 573,675 |
21 | bangladesh | 7 | frequenc_ratio | 38 | cumulonimbus_convect | 573,675 |
22 | environ | 7 | logist_regress | 37 | debris_laden_slope | 573,675 |
23 | hurrican | 7 | hazard | 35 | decis_tree_dt | 573,675 |
24 | logist_regress | 7 | risk_manag | 35 | digit_cartographi | 573,675 |
25 | malaysia | 7 | hazard_map | 32 | earth_fractur | 573,675 |
26 | adapt | 6 | hurrican | 31 | geo_informat | 573,675 |
27 | flash_flood | 6 | flash_flood | 30 | geograph_analysi | 573,675 |
28 | frequenc_ratio | 6 | land_us_plan | 30 | geograph_weight_regress | 573,675 |
29 | geomorpholog | 6 | mass_movement | 29 | hazard_cours | 573,675 |
30 | hazard_map | 6 | topographi | 29 | human_settlement | 573,675 |
31 | itali | 6 | ahp | 28 | multi_criteria_decis_analysi_mcda | 573,675 |
32 | model | 6 | itali | 28 | multicriteria_analysi | 573,675 |
33 | monitor | 6 | seismic_hazard | 28 | orograph_forc | 573,675 |
34 | seismic_hazard | 6 | spatial_analysi | 28 | participatori_map | 573,675 |
35 | sustain | 6 | sustain_develop | 28 | physic_geographi | 573,675 |
36 | ahp | 5 | sea_level_rise | 27 | primari_school | 573,675 |
37 | debri_flow | 5 | urban_geolog | 27 | river_murray | 573,675 |
38 | disast_manag | 5 | disast_manag | 26 | scenario_model | 573,675 |
39 | environment_hazard | 5 | environment_hazard | 26 | seismic_microzon | 573,675 |
40 | eros | 5 | land_cover | 26 | torrenti_rainfal | 573,675 |
41 | fire | 5 | sustain | 26 | urban_form | 573,675 |
42 | indic | 5 | geomorpholog | 25 | casualti | 562,201.5 |
43 | insur | 5 | monitor | 25 | parallel_comput | 562,201.5 |
44 | land_us_plan | 5 | analyt_hierarchi_process | 24 | support_vector_machin_svm | 562,201.5 |
45 | mass_movement | 5 | artifici_neural_network | 24 | area_with_geograph_specif | 489,536 |
46 | risk_percept | 5 | bushfir | 24 | multi_criteria_method | 489,536 |
47 | sea_level_rise | 5 | coastal_manag | 24 | dewey_john | 489,536 |
48 | suscept | 5 | flood_disast | 24 | european_polici | 489,536 |
49 | sustain_develop | 5 | land_use_plan | 23 | evidence_bas_polici | 489,536 |
50 | topographi | 5 | debri_flow | 22 | gloss_srtm_data | 489,536 |
51 | tsunami | 5 | disast_risk_assess | 22 | natur_killert_cel | 489,536 |
52 | urban | 5 | geograph_variat | 22 | orissa_india | 489,536 |
53 | analyt_hierarchi_process | 4 | insur | 22 | participatori_plan | 489,536 |
54 | artifici_neural_network | 4 | slope_stabil | 22 | spatial_heterogen | 489,536 |
55 | bushfir | 4 | adapt | 21 | spatial_homogen | 489,536 |
56 | china | 4 | analyt_hierarchi_process_ahp | 21 | white_gilbert | 489,536 |
57 | coastal_manag | 4 | casualti | 21 | land_cover | 470,065.8 |
58 | flood_disast | 4 | coastal_vulner_index | 21 | landslid_suscept | 452,160.2 |
59 | flood_hazard | 4 | environ | 21 | flood_suscept | 437,085.7 |
60 | groundwat | 4 | gis_model | 21 | global_posit_system | 437,085.7 |
61 | himalaya | 4 | himalaya | 21 | analyt_hierarch_process | 430,256.3 |
62 | infrastructur | 4 | iran | 21 | crowdsourc | 430,256.3 |
63 | iran | 4 | parallel_comput | 21 | decis_support_system_dss | 430,256.3 |
64 | land_cover | 4 | pca | 21 | eman_coeffici | 430,256.3 |
65 | land_use_plan | 4 | risk_percept | 21 | fire_weather | 430,256.3 |
66 | rainfal | 4 | support_vector_machin_svm | 21 | flood_prepared | 430,256.3 |
67 | rockfal | 4 | suscept | 21 | fuzzi_relat | 430,256.3 |
68 | slope_stabil | 4 | tsunami | 21 | human_environ_relat | 430,256.3 |
69 | spatial_analysi | 4 | environment_justic | 20 | landslid_hazard_map | 430,256.3 |
70 | turkey | 4 | flood_hazard | 20 | multi_hazard_assess | 430,256.3 |
71 | uncertainti | 4 | flood_suscept | 20 | probabl_model | 430,256.3 |
72 | urban_geolog | 4 | global_posit_system | 20 | radon_mass_exhal_rate | 430,256.3 |
73 | wildfir | 4 | hazus | 20 | 430,256.3 | |
74 | analyt_hierarchi_process_ahp | 3 | iczm | 20 | vancouv | 430,256.3 |
75 | caribbean | 3 | indic | 20 | volunt_geograph_inform | 430,256.3 |
76 | casualti | 3 | natur_disturb | 20 | bangladesh | 401,176.9 |
77 | climat_chang_adapt | 3 | rockfal | 20 | land_us_plan | 382,450 |
78 | coastal_eros | 3 | serbia | 20 | landslid | 353,191.5 |
79 | coastal_vulner_index | 3 | turkey | 20 | social_vulner | 346,514.1 |
80 | damag | 3 | environment_chang | 19 | environment_justic | 339,955.6 |
81 | databas | 3 | estuari | 19 | hazus | 339,955.6 |
82 | dea | 3 | fire | 19 | Iczm | 339,955.6 |
83 | decis_support_system | 3 | infrastructur | 19 | natur_disturb | 339,955.6 |
84 | disast_mitig | 3 | ndvi | 19 | serbia | 339,955.6 |
85 | disast_risk_assess | 3 | photogrammetri | 19 | natur_disast | 311,798.6 |
86 | ecosystem_servic | 3 | rainfal | 19 | logist_regress | 307,984.7 |
87 | emerg_manag | 3 | urban | 19 | mass_movement | 306,324.2 |
88 | emerg_respons | 3 | china | 18 | topographi | 306,324.2 |
89 | environment_chang | 3 | eros | 18 | dea_model | 299,840.8 |
90 | environment_justic | 3 | groundwat | 18 | exceed_probabl | 299,840.8 |
91 | epidemiolog | 3 | peru | 18 | landslid_monitor | 299,840.8 |
92 | estuari | 3 | uncertainti | 18 | riverbank_stabil | 299,840.8 |
93 | exposur | 3 | wildfir | 18 | urban_system | 299,840.8 |
94 | flood_suscept | 3 | caribbean | 17 | natur_hazard | 297,429.3 |
95 | gender | 3 | coastal_eros | 17 | artifici_neural_network | 293,721.6 |
96 | geograph_variat | 3 | decis_support_system | 17 | bushfir | 293,721.6 |
97 | gis_model | 3 | disast_mitig | 17 | coastal_manag | 293,721.6 |
98 | global_posit_system | 3 | ecosystem_servic | 17 | photogrammetri | 276,128.9 |
99 | hazus | 3 | liquefact | 17 | analyt_hierarchi_process | 259,166.1 |
Appendix 2: Top 99 semantic units in the semantic based results (SF, SF-SIDF, SF-SAI)
Rank | SF | Freq. | SF-SIDF | Freq. | SF-SAI | Freq. |
|---|---|---|---|---|---|---|
1 | gis; participatori_gis | 95 | gis; participatori_gis | 350.5554 | fluvial_hazard; hydrometeorolog_hazard; hazard_geographi; geoenvironment_hazard; multi_hazard; hazard_ontolog; hazard_informat; hazard; | 8,329,761 |
2 | geograph_inform_system; geograph_inform_system_gis | 74 | geograph_inform_system; geograph_inform_system_gis | 341.2582 | car_model; multiscal_model; dea_model; loglinear_model; model; ensembl_model; nois_model; traffic_model; model_chain; hidden_markov_model; mathemat_model; geochem_model; bayesian_hierarch_model; probabilist_model | 3,059,600 |
3 | natur_hazard | 64 | natur_hazard | 163.5489 | geograph_inform_system; geograph_inform_system_gis | 551,130.6 |
4 | socioeconom_vulner; socio_demograph_vulner; differenti_vulner; vulner; social_vulner; port_vulner | 52 | socioeconom_vulner; socio_demograph_vulner; differenti_vulner; vulner; social_vulner; port_vulner | 171.622 | gis; participatori_gis; | 361,425.3 |
5 | landslid; landslid_inventori | 45 | landslid; landslid_inventori | 151.6579 | socioeconom_vulner; socio_demograph_vulner; differenti_vulner; vulner; social_vulner; port_vulner | 73,343.6 |
6 | vulner_matrix; vulner; port_vulner; differenti_vulner | 40 | vulner_matrix; vulner; port_vulner; differenti_vulner | 138.9708 | hyperspectr_remot_sens; remot_sens_rs; remot_sens; satellit_remot_sens | 65,562.86 |
7 | fluvial_hazard; hydrometeorolog_hazard; hazard_geographi; geoenvironment_hazard; multi_hazard; hazard_ontolog; hazard_informat; hazard | 33 | fluvial_hazard; hydrometeorolog_hazard; hazard_geographi; geoenvironment_hazard; multi_hazard; hazard_ontolog; hazard_informat; hazard | 295.0969 | landslid; landslid_inventori | 58,894.39 |
8 | hyperspectr_remot_sens; remot_sens_rs; remot_sens; satellit_remot_sens | 30 | hyperspectr_remot_sens; remot_sens_rs; remot_sens; satellit_remot_sens | 128.6511 | natur_hazard | 52,744.62 |
9 | flash_flood; flood | 28 | flash_flood; flood | 93.62943 | vulner_matrix; vulner; port_vulner; differenti_vulner; | 51,638.82 |
10 | latent_risk; risk; predat_risk; risk_zonat | 25 | latent_risk; risk; predat_risk; risk_zonat | 86.54228 | analyt_hierarch_process; analyt_hierarchi_process; analyt_hierarch_process_ahp; analyt_hierarchi_process_ahp; fuzzi_analyt_hierarchi_process_fahp | 51,418.28 |
11 | multi_risk_assess; risk_assess; participatori_risk_assess; ecolog_risk_assess; individu_risk_assess | 24 | multi_risk_assess; risk_assess; participatori_risk_assess; ecolog_risk_assess; individu_risk_assess | 85.94491 | frequenc_ratio; likelihood_frequenc_ratio | 31,233.42 |
12 | natur_disast; natur_disast_prepared | 23 | natur_disast; natur_disast_prepared | 90.27616 | landslid_suscept; landslid_suscept_ls | 28,922.78 |
13 | chamoli_earthquak; earthquak; haiti_earthquak; chi_chi_earthquak; wenchuan_earthquak; devast_earthquak | 22 | chamoli_earthquak; earthquak; haiti_earthquak; chi_chi_earthquak; wenchuan_earthquak; devast_earthquak | 77.67505 | malaysia | 28,830.85 |
14 | presidenti_disast_declar; manmad_disast; disast; post_disast_reconstruct; disast_prepared | 22 | presidenti_disast_declar; manmad_disast; disast; post_disast_reconstruct; disast_prepared | 78.47514 | natur_disast; natur_disast_prepared | 26,796.83 |
15 | car_model; multiscal_model; dea_model; loglinear_model; model; ensembl_model; nois_model; traffic_model; model_chain; hidden_markov_model; mathemat_model; geochem_model; bayesian_hierarch_model; probabilist_model | 20 | car_model; multiscal_model; dea_model; loglinear_model; model; ensembl_model; nois_model; traffic_model; model_chain; hidden_markov_model; mathemat_model; geochem_model; bayesian_hierarch_model; probabilist_model | 178.8466 | geograph_inform; volunt_geograph_inform | 24,476.8 |
16 | climat_chang; climat_chang_adapt | 16 | climat_chang; climat_chang_adapt | 56.49095 | intrins_vulner_map; map_vulner; vulner_map; specif_vulner_map; | 24,476.8 |
17 | analyt_hierarch_process; analyt_hierarchi_process; analyt_hierarch_process_ahp; analyt_hierarchi_process_ahp; fuzzi_analyt_hierarchi_process_fahp | 11 | analyt_hierarch_process; analyt_hierarchi_process; analyt_hierarch_process_ahp; analyt_hierarchi_process_ahp; fuzzi_analyt_hierarchi_process_fahp | 66.57154 | spatial_analysi; spatial_multi_criteria_analysi; tempor_analysi | 22,947 |
18 | landslid_suscept; landslid_suscept_ls | 11 | landslid_suscept; landslid_suscept_ls | 60.24254 | flash_flood; flood; | 22,210.43 |
19 | resili | 11 | resili | 44.24584 | multi_risk_assess; risk_assess; participatori_risk_assess; ecolog_risk_assess; individu_risk_assess; | 20,684.62 |
20 | gargano_promontori_southern_itali; southern_itali; itali; western_jilin_provinc; central_liaon_provinc | 10 | gargano_promontori_southern_itali; southern_itali; itali; western_jilin_provinc; central_liaon_provinc | 46.51871 | land_cover | 20,397.33 |
21 | hurrican; hurrican_mitch; hurrican_katrina | 10 | hurrican; hurrican_mitch; hurrican_katrina | 46.65664 | latent_risk; risk; predat_risk; risk_zonat; | 19,919.27 |
22 | optim_risk_manag; risk_manag | 10 | optim_risk_manag; risk_manag | 42.97939 | nord_pas_de_calai; vulnerabilidad_de_las_instalacion_critica; santiago_de_chile; vulnerabilidad_de_la_infraestructura; | 17,483.43 |
23 | ayvalik_turkey; turkey; findik_turkey; egirdir_turkey; yenisehir_turkey; istanbul_turkey | 9 | ayvalik_turkey; turkey; findik_turkey; egirdir_turkey; yenisehir_turkey; istanbul_turkey | 47.05882 | casualti | 17,210.25 |
24 | drought | 9 | drought | 41.04273 | disast_risk_assess | 17,210.25 |
25 | geotechn_microzon_map; neotecton_map; krige_map; participatori_map; map; geomorpholog_map | 9 | geotechn_microzon_map; neotecton_map; krige_map; participatori_map; map; geomorpholog_map | 45.64016 | geograph_variat | 17,210.25 |
26 | environ; geo_environ | 8 | environ; geo_environ | 38.65165 | presidenti_disast_declar; manmad_disast; disast; post_disast_reconstruct; disast_prepared; | 17,139.43 |
27 | urban; urban_geographi; urban_terror; urban_abandon | 8 | urban; urban_geographi; urban_terror; urban_abandon | 43.32776 | chamoli_earthquak; earthquak; haiti_earthquak; chi_chi_earthquak; wenchuan_earthquak; devast_earthquak; | 16,527.3 |
28 | alborz_mountain; fagara_mountain; apuseni_mountain; changbai_mountain; mountain | 7 | alborz_mountain; fagara_mountain; apuseni_mountain; changbai_mountain; mountain | 40.06418 | land_plan; land_us_plan | 15,298 |
29 | bangladesh | 7 | bangladesh | 39.52545 | hazus; hazus_mh | 15,298 |
30 | bayesian_analysi; multicriteria_analysi; spatiotempor_analysi; discours_analysi; meta_analysi; 3d_visual_analysi | 7 | bayesian_analysi; multicriteria_analysi; spatiotempor_analysi; discours_analysi; meta_analysi; 3d_visual_analysi | 20.23169 | urban_geolog | 15,298 |
31 | binghamton_geomorpholog_symposium; geomorpholog | 7 | binghamton_geomorpholog_symposium; geomorpholog | 35.07353 | ayvalik_turkey; turkey; findik_turkey; egirdir_turkey; yenisehir_turkey; istanbul_turkey; | 15,111.44 |
32 | frequenc_ratio; likelihood_frequenc_ratio | 7 | frequenc_ratio; likelihood_frequenc_ratio | 45.20196 | alborz_mountain; fagara_mountain; apuseni_mountain; changbai_mountain; mountain; | 14,992.04 |
33 | logist_regress | 7 | logist_regress | 35.4979 | topographi | 14,709.62 |
34 | malaysia | 7 | malaysia | 44.64167 | urban; urban_geographi; urban_terror; urban_abandon; | 14,398.12 |
35 | northeast_china; fujian_china; china; northern_china | 7 | northeast_china; fujian_china; china; northern_china | 33.05976 | bangladesh | 13,881.52 |
36 | semi_natur_habitat; natur_disturb; natur_geohazard; natur_calam; natur_conserv | 7 | semi_natur_habitat; natur_disturb; natur_geohazard; natur_calam; natur_conserv | 34.80427 | rainfal; torrenti_rainfal | 13,768.2 |
37 | sustain; sustain_tourism | 7 | sustain; sustain_tourism | 36.10698 | gis_model | 13,768.2 |
38 | artifici_neural_network; neural_network | 6 | artifici_neural_network; neural_network | 33.45021 | pca | 13,768.2 |
39 | asset_manag; habitat_manag; stock_manag; wildlif_manag; self_manag; manag | 6 | asset_manag; habitat_manag; stock_manag; wildlif_manag; self_manag; manag | 29.60998 | catchment; saratel_catchment; xiangxi_catchment; loess_catchment; | 13,598.22 |
40 | big_data; data_fusion; multisensor_data_fusion; srtm_data; lidar_data; administr_data | 6 | big_data; data_fusion; multisensor_data_fusion; srtm_data; lidar_data; administr_data | 31.5207 | natur_disturb_regim; natur_disturb | 13,598.22 |
41 | cardiovascular_diseas; coronari_diseas; diarrheal_diseas; hiv_diseas_progress; diseas_progress; coronari_heart_diseas | 6 | cardiovascular_diseas; coronari_diseas; diarrheal_diseas; hiv_diseas_progress; diseas_progress; coronari_heart_diseas | 15.01788 | geotechn_microzon_map; neotecton_map; krige_map; participatori_map; map; geomorpholog_map | 12,907.69 |
42 | fire; grassland_fire | 6 | fire; grassland_fire | 28.70068 | estuari; meghna_estuari; | 12,238.4 |
43 | hazard_map | 6 | hazard_map | 34.84102 | wildland_fire_risk; fire_risk; forest_fire_risk; | 12,238.4 |
44 | land_plan; land_us_plan | 6 | land_plan; land_us_plan | 36.31175 | hazard_map; | 11,972.35 |
45 | monitor | 6 | monitor | 31.5207 | coastal_vulner_index | 11,473.5 |
46 | rainfal; torrenti_rainfal | 6 | rainfal; torrenti_rainfal | 35.67959 | dea; | 11,473.5 |
47 | sea_level; sea_level_rise | 6 | sea_level; sea_level_rise | 33.45021 | disast_risk_index; ecolog_disast_risk_index; grassland_snow_disast_risk_index; | 11,473.5 |
48 | seismic_hazard | 6 | seismic_hazard | 30.30306 | coastal_manag; urban_manag | 11,248.53 |
49 | slope; slope_movement; slope_stabil | 6 | slope; slope_movement; slope_stabil | 30.81401 | hurrican; hurrican_mitch; hurrican_katrina; | 10,623.61 |
50 | social_media; social_geographi; social_disadvantag; social; social_contact | 6 | social_media; social_geographi; social_disadvantag; social; social_contact | 32.85957 | landslid_inventori_map; landslid_map; landslid_suscept_map; | 10,623.61 |
51 | spatial_analysi; spatial_multi_criteria_analysi; tempor_analysi | 6 | spatial_analysi; spatial_multi_criteria_analysi; tempor_analysi | 38.74454 | gargano_promontori_southern_itali; southern_itali; itali; western_jilin_provinc; central_liaon_provinc; | 10,478.08 |
52 | arctic_region; region; himalayan_region; arid_region; mediterranean_region | 5 | arctic_region; region; himalayan_region; arid_region; mediterranean_region | 27.70566 | spatial; spatial_smooth; spatial_heterogen; spatial_homogen | 10,198.67 |
53 | coastal_manag; urban_manag | 5 | coastal_manag; urban_manag | 30.54558 | activ_learn | 10,198.67 |
54 | debri_flow | 5 | debri_flow | 22.99262 | anthropogen_intervent | 10,198.67 |
55 | decis_support_system; decis_support_system_dss | 5 | decis_support_system; decis_support_system_dss | 29.25644 | catastroph_theori | 10,198.67 |
56 | disast_manag | 5 | disast_manag | 27.22911 | claim; claim_payout; | 10,198.67 |
57 | eros | 5 | eros | 25.67834 | climat_variat | 10,198.67 |
58 | flash_flood_hazard; flood_hazard | 5 | flash_flood_hazard; flood_hazard | 27.70566 | communic_satellit; satellit_communic; | 10,198.67 |
59 | guangdong_provinc; shandong_provinc; hebei_provinc; jilin_provinc; western_jilin_provinc | 5 | guangdong_provinc; shandong_provinc; hebei_provinc; jilin_provinc; western_jilin_provinc | 29.73299 | crowdsourc | 10,198.67 |
60 | himalaya; kashmir_himalaya | 5 | himalaya; kashmir_himalaya | 27.70566 | cumul_fire_risk_index; fire_risk_index; | 10,198.67 |
61 | indic | 5 | indic | 29.03418 | cumulonimbus_convect | 10,198.67 |
62 | insur | 5 | insur | 25.56844 | earth_fractur | 10,198.67 |
63 | landslid_inventori_map; landslid_map; landslid_suscept_map | 5 | landslid_inventori_map; landslid_map; landslid_suscept_map | 30.25979 | flood_prepared | 10,198.67 |
64 | mass_movement | 5 | mass_movement | 29.98946 | geo_informat | 10,198.67 |
65 | po_river; river_murray; river; yangtz_river_delta | 5 | po_river; river_murray; river; yangtz_river_delta | 23.54112 | geograph_analysi | 10,198.67 |
66 | risk_percept | 5 | risk_percept | 21.88991 | geograph_weight_regress | 10,198.67 |
67 | sustain_develop | 5 | sustain_develop | 28.61727 | geospati; | 10,198.67 |
68 | topographi | 5 | topographi | 31.8869 | hazard_cours | 10,198.67 |
69 | tsunami | 5 | tsunami | 21.94227 | hazard_zone; multi_hazard_zone; | 10,198.67 |
70 | alp; apuan_alp; swiss_alp | 4 | alp; apuan_alp; swiss_alp | 23.05711 | human_environ_relat | 10,198.67 |
71 | bushfir | 4 | bushfir | 25.21309 | land_us; | 10,198.67 |
72 | catchment; saratel_catchment; xiangxi_catchment; loess_catchment | 4 | catchment; saratel_catchment; xiangxi_catchment; loess_catchment | 26.98042 | offshor_taiwan; onshor_taiwan; | 10,198.67 |
73 | central_america; central_greec; central_liaon_provinc | 4 | central_america; central_greec; central_liaon_provinc | 21.54793 | physic_geographi | 10,198.67 |
74 | coastal_area; coastal_urban_area; urban_area | 4 | coastal_area; coastal_urban_area; urban_area | 24.20783 | primari_school | 10,198.67 |
75 | cultur; cultur_geographi; cultur_heritag | 4 | cultur; cultur_geographi; cultur_heritag | 23.78639 | prison | 10,198.67 |
76 | eco_friend_method; interdisciplinari_method; geostatist_method; semi_qualit_method | 4 | eco_friend_method; interdisciplinari_method; geostatist_method; semi_qualit_method | 21.0138 | scenario_model | 10,198.67 |
77 | environment_anthropolog; environment_justic | 4 | environment_anthropolog; environment_justic | 22.30014 | 10,198.67 | |
78 | estuari; meghna_estuari | 4 | estuari; meghna_estuari | 26.55898 | urban_form | 10,198.67 |
79 | flood_disast | 4 | flood_disast | 24.43647 | vancouv | 10,198.67 |
80 | forest; minudasht_forest; oak_forest | 4 | forest; minudasht_forest; oak_forest | 22.73693 | mass_movement | 10,064.47 |
81 | fujita_scale; scale | 4 | fujita_scale; scale | 25.50952 | digit; digit_cartographi | 9834.429 |
82 | geograph_inform; volunt_geograph_inform | 4 | geograph_inform; volunt_geograph_inform | 29.33157 | flood_suscept | 9834.429 |
83 | geolog_hazard; geomorpholog_hazard | 4 | geolog_hazard; geomorpholog_hazard | 22.4405 | global_posit_system | 9834.429 |
84 | groundwat | 4 | groundwat | 20.12123 | iczm | 9834.429 |
85 | hazus; hazus_mh | 4 | hazus; hazus_mh | 27.45155 | photogrammetri | 9834.429 |
86 | human_capit; human_settlement; human_biomonitor | 4 | human_capit; human_settlement; human_biomonitor | 23.22734 | guangdong_provinc; shandong_provinc; hebei_provinc; jilin_provinc; western_jilin_provinc; | 9561.25 |
87 | infrastructur | 4 | infrastructur | 24.20783 | artifici_neural_network; neural_network | 9495.31 |
88 | integr_vulner_assess; vulner_assess | 4 | integr_vulner_assess; vulner_assess | 22.73693 | sea_level; sea_level_rise; | 9495.31 |
89 | intrins_vulner_map; map_vulner; vulner_map; specif_vulner_map | 4 | intrins_vulner_map; map_vulner; vulner_map; specif_vulner_map | 29.33157 | fujita_scale; scale; | 9414.154 |
90 | iran | 4 | iran | 21.43525 | climat_chang; climat_chang_adapt; | 8741.714 |
91 | land_cover | 4 | land_cover | 28.60228 | bushfir | 8741.714 |
92 | land_use_plan | 4 | land_use_plan | 23.05711 | decis_support_system; decis_support_system_dss | 8692.045 |
93 | natur_break; natur_geohazard; natur_calam; socio_natur | 4 | natur_break; natur_geohazard; natur_calam; socio_natur | 18.44639 | social_media; social_geographi; social_disadvantag; social; social_contact; | 8605.125 |
94 | natur_disturb_regim; natur_disturb | 4 | natur_disturb_regim; natur_disturb | 26.98042 | landsat; landsat_tm; | 8605.125 |
95 | nival_process; poisson_process; torrenti_process; geochem_process | 4 | nival_process; poisson_process; torrenti_process; geochem_process | 20.81864 | serbia | 8605.125 |
96 | nord_pas_de_calai; vulnerabilidad_de_las_instalacion_critica; santiago_de_chile; vulnerabilidad_de_la_infraestructura | 4 | nord_pas_de_calai; vulnerabilidad_de_las_instalacion_critica; santiago_de_chile; vulnerabilidad_de_la_infraestructura | 27.98568 | sustain; sustain_tourism; | 8518.205 |
97 | rockfal | 4 | rockfal | 20.63256 | indic; | 8314.13 |
98 | satellit_imag; satellit_imageri; satellit_imag_classif | 4 | satellit_imag; satellit_imageri; satellit_imag_classif | 22.58597 | environ; geo_environ; | 8025.18 |
99 | soil; soil_termiticid; soil_suction | 4 | soil; soil_termiticid; soil_suction | 16.68658 | logist_regress | 7808.354 |
Appendix 3: All 137 keywords including 33 unique TF-KAI keywords, 38 unique SF-SAI keywords, and 66 overlapping keywords
Id | Keyword | Id | Keyword | Id | Keyword | Id | Keyword | Id | Keyword | Id | Keyword |
|---|---|---|---|---|---|---|---|---|---|---|---|
0 | cross_applic | 23 | fuzzi_relat | 46 | xiangxi_catchment | 69 | geo_environ | 92 | earth_fractur | 115 | |
1 | debris_laden_slope | 24 | landslid_hazard_map | 47 | meghna_estuari | 70 | dea | 93 | geo_informat | 116 | vancouv |
2 | decis_tree_dt | 25 | multi_hazard_assess | 48 | wildland_fire_risk | 71 | geograph_inform_system_gis | 94 | geograph_analysi | 117 | volunt_geograph_inform |
3 | human_settlement | 26 | probabl_model | 49 | hazard_map | 72 | geograph_inform_system | 95 | geograph_weight_regress | 118 | bangladesh |
4 | multi_criteria_decis_analysi_mcda | 27 | radon_mass_exhal_rate | 50 | disast_risk_index | 73 | gis | 96 | hazard_cours | 119 | land_us_plan |
5 | multicriteria_analysi | 28 | environment_justic | 51 | hurrican_mitch | 74 | malaysia | 97 | participatori_map | 120 | landslid |
6 | orograph_forc | 29 | exceed_probabl | 52 | landslid_inventori_map | 75 | spatial_analysi | 98 | physic_geographi | 121 | social_vulner |
7 | river_murray | 30 | landslid_monitor | 53 | gargano_promontori_southern_itali | 76 | prison | 99 | primari_school | 122 | hazus |
8 | seismic_microzon | 31 | riverbank_stabil | 54 | claim_payout | 77 | disast_risk_assess | 100 | scenario_model | 123 | iczm |
9 | parallel_comput | 32 | urban_system | 55 | satellit_communic | 78 | geograph_variat | 101 | torrenti_rainfal | 124 | natur_disturb |
10 | support_vector_machin_svm | 33 | hydrometeorolog_hazard | 56 | cumul_fire_risk_index | 79 | frequenc_ratio | 102 | urban_form | 125 | serbia |
11 | area_with_geograph_specif | 34 | participatori_gis | 57 | geospati | 80 | remot_sens | 103 | casualti | 126 | natur_disast |
12 | multi_criteria_method | 35 | vulner_matrix | 58 | multi_hazard_zone | 81 | urban_geolog | 104 | spatial_heterogen | 127 | logist_regress |
13 | dewey_john | 36 | intrins_vulner_ma | 59 | land_us | 82 | analyt_hierarchi_process_ahp | 105 | spatial_homogen | 128 | mass_movement |
14 | european_polici | 37 | flash_flood | 60 | onshor_taiwan | 83 | coastal_vulner_index | 106 | land_cover | 129 | topographi |
15 | evidence_bas_polici | 38 | multi_risk_assess | 61 | guangdong_provinc | 84 | gis_model | 107 | landslid_suscept | 130 | dea_model |
16 | gloss_srtm_data | 39 | latent_risk | 62 | sea_level_rise | 85 | pca | 108 | flood_suscept | 131 | natur_hazard |
17 | natur_killer_t_cel | 40 | vulnerabilidad_de_la_infraestructura | 63 | fujita_scale | 86 | activ_learn | 109 | global_posit_system | 132 | artifici_neural_network |
18 | orissa_india | 41 | presidenti_disast_declar | 64 | climat_chang_adapt | 87 | anthropogen_intervent | 110 | analyt_hierarch_process | 133 | bushfir |
19 | participatori_plan | 42 | wenchuan_earthquak | 65 | social_media | 88 | catastroph_theori | 111 | crowdsourc | 134 | coastal_manag |
20 | white_gilbert | 43 | istanbul_turkey | 66 | landsat_tm | 89 | climat_variat | 112 | decis_support_system_dss | 135 | photogrammetri |
21 | eman_coeffici | 44 | changbai_mountain | 67 | sustain_tourism | 90 | cumulonimbus_convect | 113 | flood_prepared | 136 | analyt_hierarchi_process |
22 | fire_weather | 45 | urban_terror | 68 | indic | 91 | digit_cartographi | 114 | human_environ_relat |
Appendix 4: Experimental materials for testing the efficiency of the SF-SAI and TF-KAI methods
Rank | SF-SAI semantic units | SF-SAI keywords | TF-KAI unique keywords |
|---|---|---|---|
1 | fluvial_hazard; hydrometeorolog_hazard; hazard_geographi; geoenvironment_hazard; multi_hazard; hazard_ontolog; hazard_informat; hazard | hydrometeorolog_hazard | cross_applic |
2 | gis; participatori_gis | participatori_gis | debris_laden_slope |
3 | vulner_matrix; vulner; port_vulner; differenti_vulner | vulner_matrix | decis_tree_dt |
4 | intrins_vulner_map; map_vulner; vulner_map; specif_vulner_map | intrins_vulner_ma | human_settlement |
5 | flash_flood; flood | flash_flood | multi_criteria_decis_analysi_mcda |
6 | multi_risk_assess; risk_assess; participatori_risk_assess; ecolog_risk_assess; individu_risk_assess | multi_risk_assess | multicriteria_analysi |
7 | latent_risk; risk; predat_risk; risk_zonat | latent_risk | orograph_forc |
8 | nord_pas_de_calai; vulnerabilidad_de_las_instalacion_critica; santiago_de_chile; vulnerabilidad_de_la_infraestructura | vulnerabilidad_de_la_infraestructura | river_murray |
9 | presidenti_disast_declar; manmad_disast; disast; post_disast_reconstruct; disast_prepared | presidenti_disast_declar | seismic_microzon |
10 | chamoli_earthquak; earthquak; haiti_earthquak; chi_chi_earthquak; wenchuan_earthquak; devast_earthquak | wenchuan_earthquak | parallel_comput |
11 | ayvalik_turkey; turkey; findik_turkey; egirdir_turkey; yenisehir_turkey; istanbul_turkey | istanbul_turkey | support_vector_machin_svm |
12 | alborz_mountain; fagara_mountain; apuseni_mountain; changbai_mountain; mountain | changbai_mountain | area_with_geograph_specif |
13 | urban; urban_geographi; urban_terror; urban_abandon | urban_terror | multi_criteria_method |
14 | catchment; saratel_catchment; xiangxi_catchment; loess_catchment | xiangxi_catchment | dewey_john |
15 | estuari; meghna_estuari | meghna_estuari | european_polici |
16 | wildland_fire_risk; fire_risk; forest_fire_risk | wildland_fire_risk | evidence_bas_polici |
17 | hazard_map | hazard_map | gloss_srtm_data |
18 | disast_risk_index; ecolog_disast_risk_index; grassland_snow_disast_risk_index | disast_risk_index | natur_killer_t_cel |
19 | hurrican; hurrican_mitch; hurrican_katrina | hurrican_mitch | orissa_india |
20 | landslid_inventori_map; landslid_map; landslid_suscept_map | landslid_inventori_map | participatori_plan |
21 | gargano_promontori_southern_itali; southern_itali; itali; western_jilin_provinc; central_liaon_provinc | gargano_promontori_southern_itali | white_gilbert |
22 | claim; claim_payout | claim_payout | eman_coeffici |
23 | communic_satellit; satellit_communic | satellit_communic | fire_weather |
24 | cumul_fire_risk_index; fire_risk_index | cumul_fire_risk_index | fuzzi_relat |
25 | geospati | geospati | landslid_hazard_map |
26 | hazard_zone; multi_hazard_zone | multi_hazard_zone | multi_hazard_assess |
27 | land_us | land_us | probabl_model |
28 | offshor_taiwan; onshor_taiwan | onshor_taiwan | radon_mass_exhal_rate |
29 | guangdong_provinc; shandong_provinc; hebei_provinc; jilin_provinc; western_jilin_provinc | guangdong_provinc | environment_justic |
30 | sea_level; sea_level_rise | sea_level_rise | exceed_probabl |
31 | fujita_scale; scale | fujita_scale | landslid_monitor |
32 | climat_chang; climat_chang_adapt | climat_chang_adapt | riverbank_stabil |
33 | social_media; social_geographi; social_disadvantag; social; social_contact | social_media | urban_system |
34 | landsat; landsat_tm | landsat_tm | |
35 | sustain; sustain_tourism | sustain_tourism | |
36 | indic | indic | |
37 | environ; geo_environ | geo_environ | |
38 | dea | dea |
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Hu, K., Wu, H., Qi, K. et al. A domain keyword analysis approach extending Term Frequency-Keyword Active Index with Google Word2Vec model. Scientometrics 114, 1031–1068 (2018). https://doi.org/10.1007/s11192-017-2574-9
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DOI: https://doi.org/10.1007/s11192-017-2574-9