15. A computer system for identifying one or more topics or topic domains or attributes related to a text content, comprising: a computer processor operable to receive a text content comprising one or more words or phrases or sentences as terms, and to tokenize the text content into one or more tokens, each being an instance of a term in the text content; identify a grammatical attribute, or a semantic attribute, or an external term frequency associated with the one or more tokens or terms in the text content, wherein the grammatical attribute includes at least a subject, a predicate or part of a predicate, a modifier in a phrase, a head of a phrase, a sub-phrase of a phrase, an object, a noun, a verb, an adjective, or an adverb, wherein the semantic attribute includes at least semantic roles and attribute values, wherein the external term frequency is obtained from text contents other than the received text content; determine an importance measure for each token or term based on the grammatical attribute, or the semantic attribute, or the external term frequency; receive one or more datasets, wherein each dataset is associated with a name or description representing an object, wherein the object comprises a physical object or a concept, a topic, a topic domain, or a pre-defined attribute, wherein each dataset comprises one or more words or phrases as names of properties associated with the corresponding object, wherein the names of properties represent other objects or concepts or topics or attributes related to the object, wherein the names of properties collectively represent a type of definition or representation of the object; match at least two tokens or terms in the text content with at least two property names in each of the one or more datasets; produce, for each of the one or more datasets, a score based at least on the importance measure of each token or term that matches a property name in the dataset, when the importance measure is in the form of a term importance score that is calculated based on the external frequency, or based on the grammatical attribute, or based on the semantic attribute or attribute value, and when the score based on the importance measure is in the form of a relevance score, the relevance score is produced as a function of the term importance score; select one or more names or descriptions of the one or more datasets as relevant objects or topics or topic domains or attributes to the text content if the corresponding score is above a predefined threshold; and display, or provide an instruction to display in a user interface, or to store in the computer storage, the selected one or more names or descriptions, or the score associated with the one or more selected names or descriptions, wherein the function of the score includes serving as a quantitative measure of relevance between the text content and the selected one or more names or descriptions of the objects, or topics or topic domains or attributes.
15. A computer system for identifying one or more topics or topic domains or attributes related to a text content, comprising: a computer processor operable to receive a text content comprising one or more words or phrases or sentences as terms, and to tokenize the text content into one or more tokens, each being an instance of a term in the text content; identify a grammatical attribute, or a semantic attribute, or an external term frequency associated with the one or more tokens or terms in the text content, wherein the grammatical attribute includes at least a subject, a predicate or part of a predicate, a modifier in a phrase, a head of a phrase, a sub-phrase of a phrase, an object, a noun, a verb, an adjective, or an adverb, wherein the semantic attribute includes at least semantic roles and attribute values, wherein the external term frequency is obtained from text contents other than the received text content; determine an importance measure for each token or term based on the grammatical attribute, or the semantic attribute, or the external term frequency; receive one or more datasets, wherein each dataset is associated with a name or description representing an object, wherein the object comprises a physical object or a concept, a topic, a topic domain, or a pre-defined attribute, wherein each dataset comprises one or more words or phrases as names of properties associated with the corresponding object, wherein the names of properties represent other objects or concepts or topics or attributes related to the object, wherein the names of properties collectively represent a type of definition or representation of the object; match at least two tokens or terms in the text content with at least two property names in each of the one or more datasets; produce, for each of the one or more datasets, a score based at least on the importance measure of each token or term that matches a property name in the dataset, when the importance measure is in the form of a term importance score that is calculated based on the external frequency, or based on the grammatical attribute, or based on the semantic attribute or attribute value, and when the score based on the importance measure is in the form of a relevance score, the relevance score is produced as a function of the term importance score; select one or more names or descriptions of the one or more datasets as relevant objects or topics or topic domains or attributes to the text content if the corresponding score is above a predefined threshold; and display, or provide an instruction to display in a user interface, or to store in the computer storage, the selected one or more names or descriptions, or the score associated with the one or more selected names or descriptions, wherein the function of the score includes serving as a quantitative measure of relevance between the text content and the selected one or more names or descriptions of the objects, or topics or topic domains or attributes. 16. The computer system of claim 15 , wherein the text content is a search query, a webpage, a blog, an email, an SMS message, a transcript from an audio or text conversation, a user comment or chat message entered on a website or on a social network page, or in a user interface of a computing or communication device, wherein the selected topic or domain is relevant for advertisements, wherein the computer processor is further operable to: display in a user interface, or provide an instruction to display, an advertisement in connection with the text content, wherein the user interface includes a web user interface, a social network page, a chat screen, or an email interface, or as an audio message through an audio device, on a computing or communication device including a desktop or a notebook computer, a mobile or hand-held device, a cloud-based device, or a mobile or land phone.