E-viri
Recenzirano
Odprti dostop
-
Fang, Qixiang; Nguyen, Dong; Oberski, Daniel L.
EPJ data science, 07/2022, Letnik: 11, Številka: 1Journal Article
Text embedding models from Natural Language Processing can map text data (e.g. words, sentences, documents) to meaningful numerical representations (a.k.a. text embeddings). While such models are increasingly applied in social science research, one important issue is often not addressed: the extent to which these embeddings are high-quality representations of the information needed to be encoded. We view this quality evaluation problem from a measurement validity perspective, and propose the use of the classic construct validity framework to evaluate the quality of text embeddings. First, we describe how this framework can be adapted to the opaque and high-dimensional nature of text embeddings. Second, we apply our adapted framework to an example where we compare the validity of survey question representation across text embedding models.
Vnos na polico
Trajna povezava
- URL:
Faktor vpliva
Dostop do baze podatkov JCR je dovoljen samo uporabnikom iz Slovenije. Vaš trenutni IP-naslov ni na seznamu dovoljenih za dostop, zato je potrebna avtentikacija z ustreznim računom AAI.
Leto | Faktor vpliva | Izdaja | Kategorija | Razvrstitev | ||||
---|---|---|---|---|---|---|---|---|
JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
Baze podatkov, v katerih je revija indeksirana
Ime baze podatkov | Področje | Leto |
---|
Povezave do osebnih bibliografij avtorjev | Povezave do podatkov o raziskovalcih v sistemu SICRIS |
---|
Vir: Osebne bibliografije
in: SICRIS
To gradivo vam je dostopno v celotnem besedilu. Če kljub temu želite naročiti gradivo, kliknite gumb Nadaljuj.