The etymolog of the word is unknown. There are, however, several myths. The word has alledgedly been around since around 1400.
The anthropology of religion involves the study of religious institutions in relation to other social institutions, and the comparison of religious beliefs and practices across cultures.]citation needed[ Modern anthropology assumes that there is complete continuity between magical thinking and religion, and that every religion is a cultural product created by the human community that practices it.
Microsoft Word is a word processor developed by Microsoft. It was first released in 1983 under the name Multi-Tool Word for Xenix systems. Subsequent versions were later written for several other platforms including IBM PCs running DOS (1983), the Apple Macintosh (1985), the AT&T Unix PC (1985), Atari ST (1988), SCO UNIX (1994), OS/2 (1989), and Windows (1989). Commercial versions of Word are licensed as a standalone product or as a component of Microsoft Office, Windows RT or the discontinued Microsoft Works Suite. Freeware editions of Word are Microsoft Word Viewer and Word Web App on SkyDrive, both of which have limited feature sets.
Religion and mythology differ but have overlapping aspects. Both terms refer to systems of concepts that are of high importance to a certain community, making statements concerning the supernatural or sacred. Generally, mythology is considered one component or aspect of religion. Religion is the broader term: besides mythological aspects, it includes aspects of ritual, morality, theology, and mystical experience. A given mythology is almost always associated with a certain religion such as Greek mythology with Ancient Greek religion. Disconnected from its religious system, a myth may lose its immediate relevance to the community and evolve—away from sacred importance—into a legend or folktale.
In computational linguistics, word-sense disambiguation (WSD) is an open problem of natural language processing, which governs the process of identifying which sense of a word (i.e. meaning) is used in a sentence, when the word has multiple meanings. The solution to this problem impacts other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, inference et cetera.
Research has progressed steadily to the point where WSD systems achieve sufficiently high levels of accuracy on a variety of word types and ambiguities. A rich variety of techniques have been researched, from dictionary-based methods that use the knowledge encoded in lexical resources, to supervised machine learning methods in which a classifier is trained for each distinct word on a corpus of manually sense-annotated examples, to completely unsupervised methods that cluster occurrences of words, thereby inducing word senses. Among these, supervised learning approaches have been the most successful algorithms to date.
Algeria · Nigeria · Sudan · Ethiopia · Seychelles
Uganda · Zambia · Kenya · South Africa
Afghanistan · Pakistan · India
Nepal · Sri Lanka · Vietnam
China · Hong Kong · Macau · Taiwan
North Korea · South Korea · Japan
Malaysia · Singapore · Philippines · Thailand