You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A Review of Text Watermarking: Theory, Methods, and Applications 
Chapter Title:  B. LINGUISTIC-BASED APPROACH 
1. Abstract of Cited Paper (BIB001):  In this paper we discuss natural language watermarking, which uses the structure of the sentence constituents in natural language text in order to insert a watermark. This approach is different from techniques, collectively referred to as "text watermarking," which embed information by modifying the appearance of text elements, such as lines, words, or characters. We provide a survey of the current state of the art in natural language watermarking and introduce terminology, techniques, and tools for text processing. We also examine the parallels and differences of the two watermarking domains and outline how techniques from the image watermarking domain may be applicable to the natural language watermarking domain. 
2. Abstract of Cited Paper (BIB002):  We propose a method for watermarking texts of arbitrary length using natural-language semantic structures. For the key of our approach we use the linguistic semantic phenomenon of presuppositions. Presupposition is the implicit information considered as well-known or which readers of the text are supposed to treat as well-known; this information is a semantic component of certain linguistic expressions (lexical items and syntactical constructions called presupposition triggers). The same sentence can be used with or without presupposition, or with a different presupposition trigger, provided that all the relations between subjects, objects and other discourse referents are preserved - such transformations will not change the meaning of the sentence. We define the distinct rules for presupposition identification for each trigger and regular transformation rules for using/non-using the presupposition in a given sentence (one bit per sentence in this case). Isolated sentences can carry the proposed watermarks. However, the longer is the text, the more efficient is the watermark. The proposed approach is resilient to main types of random transformations, like passivization, topicalization, extraposition, preposing, etc. The web of resolved presupposed information in the text will hold the watermark of the text (e.g. integrity watermark, or prove of ownership), introducing "secret ordering" into the text structure to make it resilient to "data loss" attacks and "data altering" attacks. 
3. Abstract of Cited Paper (BIB003):  We present a robust and adaptive-capacity watermarking algorithm for agglutinative languages. All processes, including the selection of sentences to be watermarked, watermark embedding, and watermark extraction, are based on syntactic dependency trees. We show that it is more robust to use syntactic dependency trees than the surface forms of sentences in text watermarking. For the agglutinative languages, we embed watermark using the two main characteristics of the languages. First, because a word consists of several morphemes, we can watermark sentences using morphological division/combination without deep linguistic analysis. Second, they permit relatively free word order, so we can move a syntactic constituent within its clause. Finally, to increase the information-hiding capacity, we adaptively compute the number of watermark bits to be embedded for each sentence. ::: ::: We perform three kinds of evaluation: perceptibility, robustness, and capacity of our method. High capacity is achieved by dynamically determining possibly embedded watermark bits for each sentence. The secret rank based on a syntactic dependency tree strengthens robustness of our method. Finally, we show that the displacement of syntactic constituents and morphological division/combination does not affect the style and naturalness of the text. Copyright © 2011 John Wiley & Sons, Ltd. 
4. Abstract of Cited Paper (BIB004):  In recent decade Internet has been emerged as an eye-catching, meteoric and cost-effective medium for distribution of electronic information than the classical one. This initiation and increasing escalation of Internet has caused the information to be paperless and the makeover into electronic compared to the conventional paper distribution. As the information may be available worldwide on the Internet, it is liable to many kinds of threats as illegal copying, distribution, tampering, authentication etc. Till now, the electronic information can be secured by using different techniques like steganography, cryptography, watermarking. In text watermarking various techniques are implemented for English, Chinese, Turkish and Arabic language text using different methods. Our paper includes a novel watermarking technique for English language text documents. We have proposed an algorithm which is based on English grammatical words and a suitable encryption method. English is commercial language which is widely used across the world. We have focused on grammatical rules like conjunctions, pronouns and modal verbs to generate encrypted watermark message. The resulted technique is tested for various websites for verification. 
5. Abstract of Cited Paper (BIB005):  This paper proposes a new approach for text watermarking that uses the semantic roles to embed watermark information. The technology of natural language processing is applied to find and label the three types of semantic roles A0, A1 and ADV in a text. A watermark message is converted into the hexadecimal Unicode and then compressed with the Huffman encoding to form a digit string that consists of the digits 0, 1 and 2. Let the three types of the semantic roles correspond to the three kinds of the digits one to one. The watermark digits are embedded by mapping each digit into the location of a semantic role of the corresponding type. The algorithm does not make any change to the format and content of a text. It has good features of concealment and robustness and can resist various text format transformations and watermark attacks.

Literature Review:
The linguistic-based approach is a natural language-based method, which works by making changes to the syntactic and semantic nature of the cover text in order to embed the watermark BIB006 , BIB002 . The watermark is embedded in such a way that the structure and meaning of the text remain unchanged. Most of the linguistic-based watermarking methods make use of the semantic or syntactic transformation or a combination of both, depending on the language of the text BIB005 . According to the syntactic approach, words in the set are manipulated to hide data. The verbs, nouns, adjectives, pronouns, prepositions, synonyms, and other grammatical features of the text content are utilized in order to hide the watermark message. These grammatical alterations are done without affecting the original meaning of the text. The order of the words in the sentences can also be rearranged to hide bits. This can be done by altering the text structure and embed the watermark, such as moving the adverbial phrase, adding the subject or changing the sentence from active into passive clause. One of the early methods following the syntactic-based approach uses syntactic tree and transformation  ,  , BIB001 . This pioneer technique has inspired other researchers to create other equally unique and reliable methods. Many other syntactic-based methods have since then been proposed, thus expanding the watermarking technique  - BIB004 . Following the semantic-based approach, the data are hidden by manipulating the words in the text as watermark. This includes methods such as synonym substitution, algorithms based on noun-verbs, algorithms based on typos, acronyms and abbreviations, algorithms based on linguistic approaches of presuppositions, and algorithms based on text-meaning representational strings. This line of approach depends on the type of language itself by using its vocabulary, grammar or structure in order to hide the watermark BIB006 ,  - BIB003 .