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In the query specification part of the information access process, the searcher expresses an information need by converting their internalized, abstract concepts into language, and then converting that expression of language into a query format that the search system can make use of.
Queries over collections of textual information usually take on a textual form (querying against multimedia is discussed in Chapter 12). In older bibliographic search systems, users could only search over metadata that hinted at the underlying contents. Statistics on query length and composition have been recorded since early in the Web's existence. In the early days of the Web, search engines used statistical ranking functions, but these did not work well with the short keyword queries that Web searchers were writing.
As discussed above, in Web search engines, keyword specification and matching has become the norm. Rather than generating an answer from scratch, question answering systems attempt to link a natural language query to the most pertinent sentence, paragraph, or page of information that has already been written. The Armies of the Night (1968), a personal narrative of the 1967 peace march on the Pentagon, won Mailer the Pulitzer Prize and the National Book Award. Thus the two sentences link together the relevant noun phrases and the system hypothesized (correctly) from the title of the article in which the sentences appear that Norman Mailer was the answer. Major Web search engines currently do not support full-sentence queries or question answering, most likely because the technology still is not reliable enough to present in mature products. An interesting aspect of question answering that differentiates it from standard information retrieval is that the answer of interest contains words that are not in the query.
Another form of text-based querying is one in which the user requests that the system find documents that are substantially similar to a very long query or a user-supplied document. This desiderata of high recall was embodied in the TREC competition ad hoc ranking task (TREC is discussed in Chapter 2), where the goal was to retrieve 1000 relevant documents for every query.
For long queries, it is unlikely that every term will be found in one document within a collection, and so are best served by statistical ranking algorithms which apply empirically determined weights to each query term, and combine them statistically to provide a ranking. It is unclear how realistic it is to expect people to search for documents that are similar to other documents.
Search engine ranking algorithms must walk a fine line between making transformations that are hidden but helpful and making the user feel that the system is inscrutable.
Application of Boolean operators, comparing a search engine that automatically OR'd all terms versus one that AND'd terms. Stopword removal, comparing a system that removed stopwords versus one that did not, on the query to be or not to be (all stopwords). Suffix term expansion, comparing a search engine that does the expansion versus one that does not (in this case the query was run which would be expanded to running and runner).
Term order sensitivity, comparing a search engine that changes results based on term order and proximity versus one that does not consider either property. These results suggest that stemming is useful, but removing stopwords can be hazardous from a usability perspective. Another way search systems use query transformations is to show them as suggestions for revising the query. Today, the standard interface for query specification is an entry form and an activation button.
Some interfaces allow the searcher to cut-and-paste long swaths of text into the search box, whereas others present short entry forms and limit the number of terms that the system will accept for processing. The wording above the text box can influence the kind of information that searchers type in.
After many years of small search forms, it has recently become fashionable on many Web sites to make the font in the search box entry form very large and colorful, thus drawing attention to the search facility.
When presenting a query interface, it is important not to force the user to make selections before offering a search box. Chapter 6 discusses interfaces for suggesting terms to augment the user's query after they have received results. Some dynamic term suggestion systems show only query suggestions whose prefix matches what has been typed so far. Information Processing and Management, 43(3), 2007.">White and Marchionini, 2007 compared this approach to a baseline system with no feedback (using Google Web search with identifying information removed) and another version of their system in which term suggestions are shown alongside the search results, after the query is entered (standard term suggestions). Satisfaction scores revealed that participants found the baseline to be more effective and more usable, but found the dynamic suggestions to be more engaging and more enjoyable.
Information Processing and Management, 43(3), 2007.">White and Marchionini, 2007 point out the potential danger in showing query term suggestions before retrieval results are seen, as the suggestions can lead the searcher down an erroneous path. Before the rise of the Web, most commercial full-text systems and most bibliographic systems supported only Boolean and command-based queries. The question mark indicates a request for stemming match and the (W) notation requests that the terms be located adjacent to each other and in the order specified.
Most people who used Boolean command-line systems had extensive training on their use, and often were willing to spend time carefully formulating their queries, especially if they were charged by the query or by the minute. One problem with Boolean queries is that their strict interpretation tends to yield result sets that are either too large, because the user includes many terms in a disjunct, or are empty, because the user conjoins terms in an effort to reduce the result set.
Boolean queries are also problematic because most people find the basic semantics counter-intuitive. Another problem with pure Boolean systems is they do not rank the retrieved documents according to similarity to the query. Despite the generally poor usability of Boolean operators, most search engines support notation using AND, OR, and NOT, as well as characters for wildcarding, stemming, and range specification for dates. One technique for imposing an ordering on the results of Boolean queries is post-coordinate or quorum-level ranking [Ch. Another approach to improving results with Boolean queries is to have the searcher break their query up into different facets, that is, different topics, and specify each facet with a set of terms combined into a disjunction. Information Retrieval (SDAIR'96), Las Vegas, NV, 1996.">Hearst, 1996 showed that when at least one representative term from each facet is required to be in close proximity with one another, the resulting precision is very high.
In command-line based interfaces, Boolean operators and their operands are typically typed on one line, and combined using parentheses (see Figure 4.10a). By serving a massive audience possessing little query-specification experience, the designers of Web search engines devised what were intended to be more intuitive approaches to Boolean query specification. Another early web-based solution was to allow syntactically based query specification, but to provide a simpler or more intuitive syntax.
Researchers have developed many clever interface designs to improve Boolean query specification via visual interfaces. As discussed above, the major search engines offer a number of operators that can be applied to queries to make them more focused and exact.
2007.">White and Morris, 2007 studied interaction logs of nearly 600,000 users issuing millions of queries over a period of 13 weeks in 2006.
2007.">White and Morris, 2007 study described above, they partitioned users into experts and non-experts based on whether or not they had used operators in their queries. There is evidence that Web search engine ranking algorithms have been successful at compensating for the fact that their users do not use query operators. 2003.">Eastman and Jansen, 2003 studied the effects of removing search operators from 100 queries selected from query logs and compared the resulting documents to those retrieved by the advanced query. The functionality of command languages allows selection of collections to search over, resources to use (including thesauri), fields to search over, and format of results display. A common strategy for dealing with this problem, employed in early systems with command-line based interfaces, and in web-based library catalogs, was for the system to encourage the user to create a series of short queries, show the number of documents returned for each, and allow the user to combine those queries that produce a reasonable number of results (DialogWeb Command Search Tutorial.
To use these older systems to their fullest, users also needed to know the names of the different fields to query against, and the names of the sources they wanted to search over. Search engines typically supply a forms-based interface to aid with command specification, in addition to supporting free typing of the commands within the main entry form. Interestingly, Web search engines have recently been building command languages into their query specification abilities. These commands are associated with what is known as search shortcuts : specialized searches for commonly sought types of information such as weather, stock quotes, and airplane flight status information. The query is the bridge between the user's current understanding of their information need and the information access system. This chapter discussed two main aspects of query specification: the kind of information supplied by the searcher and the style of interface used for expressing that information.
Keyword queries, Natural language queries, including queries as questions, Paragraphs of text, Queries containing Boolean operators, and Queries with command-based syntax.
The chapter discussed how textual queries are modified by the underlying search system, including stemming and stopword removal. The decline of syntax-driven command languages (except for use by specialists) provides an instructive example of how interfaces that were originally designed to be easy to implement in a computer are being replaced by interfaces that are intuitive for users. In future it is likely that query specification by spoken language will become increasingly popular; this is discussed in the section on mobile search in Chapter 12. System Center Orchestrator 2012: How to convert flattened data into multi-value in a very easy way! Part of this runbook has to find a user in the active directory, and afterwards find his manager’s email address, before sending an email to the manager. 20th Nov 2015Azure automation: Start-AutomationRunbook – New simple way to start runbook jobs from within a runbook!
12th Oct 2015Azure Automation: Script for downloading and preparing AzureRM modules for Azure Automation! This is a place to express personal thoughts about DNNPlatform, the community and its ecosystem.
Query specification input spans a spectrum from full natural language sentences, to keywords and key phrases, to syntax-heavy command language-based queries. These include command line interfaces, graphical entry form-based interfaces, and interfaces for navigating links. Keyword queries consist of a list of one or more words or phrases -- rather than full natural language statements -- whose intention is to find documents containing those words that are likely to be relevant to the user's information need.
These measures have shown that the average query length has grown over time, and the percentage of one-word queries has shrunk.

Furthermore, searchers were not usually interested in high recall for the kinds of information available on the Web.
However, when only a small collection of documents is available, a ranking algorithm that automatically requires all terms in a query to be present in the retrieved documents will end up with empty results sets (and very frustrated users) much of the time.
The search engine under study produced empty results sets with this kind of query, and so the children had to unlearn the question-asking approach. Finally, in the early days of the Web, the search engine AskJeeves (now Ask) purported to allow people to ask natural language questions.
They assumed that if their first attempt failed then either they were incapable of searching or the system did not contain information relevant to their interest.
The main reason search engines did not originally support automated question answering is that the technology did not exist to do so in a robust, scalable manner.
For several years starting in 1999, the track focused on factoid questions: fact-based short-answer questions such as What Spanish explorer discovered the Mississippi? They differ from standard search engines in that they make use of the structure of the question and of the text from which the answers are drawn.
It then attempted to find sentences within encyclopedia articles that contain noun phrases that appear in the question, since these sentences are likely to contain the answer to the question. In 1969 Mailer ran unsuccessfully as an independent candidate for mayor of New York City. The system used a standard IR search to find the most likely FAQ (frequently asked questions) files for the question and then matched the terms in the question against the question portion of the question-answer pairs. There are a number of startup companies that build on this research and attempt to support natural language querying and question answering using scalable natural parsing and other computional linguistics technologies. However, as discussed in Chapter 1, some are becoming more adept at responding to long queries. Thus boldfacing the query terms in answer to a question is not the right thing to do -- rather, it is the answer that should be highlighted. To remove effects of incorrect answers, they used a system that produced only correct answers, drawn from an online encyclopedia. They also found that people judging relevance prefer results of different lengths, depending on the type of query. This kind of query was much studied in the information retrieval research literature in the 1980s-1990s.
In the TREC scoring, what mattered was whether or not a document had been judged relevant, not how relevant it was, nor how much new information it brought beyond what had already been seen. Some systems automatically normalize morphological variants of words, that is, convert a query on dogs to one on (dog OR dogs) or convert building to (build OR building) (the latter may lead to poor results, because the noun form of build is conflated with the verb form derived from building). Fourteen participants were asked to issue one pre-specified query across two search engines for each of four transformation types: Boolean operators, stopword removal, suffix expansion, and term order variation.
Participants were surprised at the lack of results pertaining to athletics for the engine that did not do term expansion, and only 3 participants were able to explain the results in a manner related to suffix expansion. It also suggests that certain features, such as taking order and proximity into account, can be used to improve the results without confusing users despite the fact that they may not be aware of or understand those transformations. The label on the button ranges from Go to Search to Fetch, and Microsoft's search engine dispenses with the textual label entirely, instead showing only a magnifying glass icon (see Figure 4.1a).
In recent years, Web browsers have implemented support for Web search directly into the address bar, and the Chrome browser has gone so far as to eliminate the distinction between an address bar and the query form altogether. For instance, the search dialogue box for Microsoft Windows XP forces the user to decide which type of information, in terms of file format, they want to search over before seeing a search box (see Figure 4.5). More recently, interfaces have appeared that suggest query terms dynamically, as the user enters them. An example from Microsoft in which only the first word in the query is matched against past queries.
Figure 4.6 shows an example from Microsoft's dynamic query suggestions interface, which shows frequent queries whose first words contain the prefix that has been typed so far, canc, including cancer, cancun weather, and cancel. After the user types a word and presses the keyboard space bar, the system queries a Web search engine and extracts terms from the surrogates for the 10 top-ranked documents. The study consisted of 36 students who compared the interfaces in a within-participants design.
Post-study questionnaires suggested that if the response time for the query suggestions had been faster, participants would have found them more useful. They cite as an example the high prevalence of the suggested term ride for the query Who was the first female astronaut in space?. A typical example, drawn from commands from the Dialog Pocket Guide 2006 (Dialog Command Language Pocket Guide. The sequence of terms separated by OR's are to be treated as a disjunction; two long disjunctions are connected by an AND, or conjunction operator.
Thus, the users of these systems may not have had problems with the complexity of this syntax. This problem occurs in large part because the user does not know the contents of the collection or the role of terms within the collection. Many English-speaking users assume everyday meanings are associated with Boolean operators when expressed using the English words AND and OR, rather than their logical equivalents.
Combining faceted queries with quorum ranking yields a situation intermediate between full Boolean syntax and free-form natural language queries. The user enters one topic per entry line, where each topic consists of a list of semantically related terms that are combined in a disjunct. Although Web search engines support use of operators directly in the query box, they usually also supply a graphical form-based method for using filters and restrictions.
In the mid-1990s, the AltaVista Web search engine introduced the mandatory operator, meaning that the results retrieved must include the query term, indicated with a + as a prefix before the required word. These attempts at visualizing Boolean queries are discussed in Chapter 10, but have not been widely adopted in practice. However, Web log statistics show that only a small fraction of queries take advantage of these operators. None of the participants used the negation operator -, although at least one put a space before the hyphen in what was intended to be a hyphenated term: lactose intolerant -recipes, thus ensuring that no relevant results were returned. They found significant differences in search behaviors between these two groups; the experts had different behavior when navigating search results, and they were more successful at eliciting and clicking on relevant documents. Those with information seeking professions were more likely to say they use Boolean and other operators. They found the use of most query operators had no significant effect on coverage, relative precision, or ranking, although the impact did vary depending on the search engine. Compounding this problem, despite the fact that the command languages for the two main online bibliographic systems at UC Berkeley had different but very similar syntaxes, after more than 10 years one of the systems still reported an error if the author field was specified as PA instead of PN, as is done in the other system. For example, in the early Dialog system, each query produced a resulting set of documents that was assigned an identifying name. The following more complex example, also derived from the Dialog Pocket Guide 2006 (Dialog Command Language Pocket Guide. In the late 1990s, systems like Dialog and online library catalogs upgraded to web-based forms interfaces, thus lessening the memory burden. The results of these shortcuts are also shown, when appropriate, in some search results listings. The problem with command languages like these, of course, is that the user must remember a command correctly in order to use it, although a current research trend is to support ever-more flexible variations on command languages. Query specification today is primarily accomplished by the user typing keyword queries into an entry form or following hyperlinks at a known Web site (the use of links as a form of query specification is discussed in detail in Chapter 8). The chapter also described graphical entry forms for query specification, and discussed the increasing importance and popularity of dynamic term suggestions that appear as the user types their query.
It is impressive that today people respond in surveys saying that Web search engines are easy to use; for the first few years of their existence, people complained that their behavior was confusing. It is also likely that long queries, including queries structured as questions, will continue to increase in usage as the algorithms responding to them improve. First of I spend some time complaining, but when I was done crying I figured something out! In addition to our commercial CMS and social community solutions, DNN is the steward of the DotNetNuke Open Source Project. Using a standard library catalog, a searcher who was interested in discussions of narwhales in literature would not have been able to discover that Moby Dick contains several discussions of these unicorn-like fish. Example English keyword queries (from Google Trends and Dogpile SearchSpy, November 1, 2008) include flip cam, fresh chilli paste recipes, and video game addiction.
Searchers also found statistical ranking on short queries to be confusing, not understanding why, say, the highest ranked documents might contain only one query term out of three (The New York Times, September 3, September 3 1998.">Lake, 1998).
With a larger document pool, a query on any combination of three or fewer terms is likely to return a result, even if all the terms are conjoined.
Evidence from the literature suggests that asking questions using natural language is a more intuitive input method, and that people who are new to using search engines tend to assume that asking a question is the right way to start.
Although it never really supported this functionality in a robust and scalable way, many people were attracted to the engine because they thought it would be able to answer questions.
Thus, novice searchers must learn to expect that they must scan a search results list, navigate through Web sites, and read through Web pages to try to find the information they seek. For example, the startup Powerset (recently acquired by Microsoft) successfully responds to questions like What did Steve Jobs say about the iPod? Natural language queries are also likely to become an important supplement for organizations' web sites and for software products, to more effectively handle customer questions. A question also arises as to what kind of and how much context to show surrounding the answer. They found that most participants (53%) preferred paragraph-sized chunks, noting that a sentence did not supply much more information beyond the exact answer, and a full document was oftentimes too long.
The emphasis was on producing retrieval results with high recall, since finding all relevant documents can be quite useful for scholars trying to do thorough literature reviews, legal professionals trying to find all information about a case (Communications of the ACM, 28(3), 1985.">Blair and Maron, 1985), and intelligence analysts trying to assess a situation. Queries and search engines were carefully chosen to exaggerate and highlight the effect of the query transformation, and participants were asked to first state what they thought would happen before seeing the results.
Eight out of 14 participants expected the system to return many results related to both scuba and snorkeling but few if any mentions of Aruba. After seeing the empty results for one engine, 3 participants assumed the search engine did not contain literature in its collection or had a different collection, 6 expressed low expectations for good results because of the commonality of the words, but only 3 expressed the notion of the search engine dropping the results. Other studies suggest that it is better to show potential transformations to users and let them decide whether or not to use them than to do them explicitly; however, if automatic transformations are unlikely to lead to misconceptions, they can be beneficial.

To test this hypothesis, Franzen and Karlgren, 2000 designed two different query entry form boxes. In that browser, everything is assumed to be a query to a Web search engine unless URL syntax is used explicitly. An entry form should immediately be offered that defaults to searching all file types, with an option to refine. In some cases, these dynamic term suggestions appear before the searcher has seen any retrieval results, and in others, the system dynamically shows documents that match the characters typed so far, adjusting the results list as more characters are typed.
The rapid spread of this facility suggests that dynamic real-time term suggestions are becoming the norm. Using pre-defined queries, the study distinguished between known-item searches and open-ended exploratory searches, hypothesizing that term expansion would be more effective for the latter. Many commented negatively on the delay (1.8 seconds average) between hitting the space bar and seeing the suggestions. The correct answer is Soviet cosmonaut Valentina Tereshkova, but mention of Sally Ride, the first American woman in space, is frequent in the retrieved document summaries. To inexperienced users, using AND implies the widening of the scope of the query, because more kinds of information are requested in such a query.
Commercial systems with Boolean queries usually order documents according to some kind of descriptive metadata, usually reverse chronological order.
The most commonly used operator on the Web is the double-quote operator "", used to surround adjacent words, as in "San Francisco", which signifies that the enclosed terms must be found directly adjacent in the retrieved text.
In this approach, documents are ranked according to the size of the subset of the query terms they contain. Instead, facets are now widely used in navigation interfaces for collections (see Chapter 8).
At that time, Web search results were ranked using statistical algorithms, and so the top results for a three-keyword query might not contain all of the query terms (if, for example, the algorithm chose to rank a document with 100 occurrences of the first keyword ahead of a document with one occurrence of all three keywords). The one exception is for database query specification, an area in which graphical command building applications have become popular. It is difficult to obtain accurate statistics from current Web search engines, so below are reported a set of statistics that have been gleaned by researchers using the few available open Web log resources.
16% of the participants used double quotation marks, but a few of them used them incorrectly or superfluously. This lack of flexibility in the syntax was characteristic of older interfaces designed to suit the system rather than its users.
However, they are also complex and difficult to use, requiring the user to remember and accurately type cryptic commands. Rather than returning a list of titles themselves, Dialog showed the result set number with a listing of the number of matched documents. The number of results found for each part of the query are shown on the following three lines, along with an automatically named results set S1. Figure 4.10 shows versions of the query specification form and results modification forms, which still bear a great deal of resemblance to their TTY-based counterparts. These allow both for traditional uses of search commands, such as restricting the query to search over a particular field, as well as for more innovative commands that map to very specific information needs.
Other query modifications such as spelling suggestions and term expansions are discussed in detail in Chapter 6.
Not only did the algorithms change, but also the assumptions behind them changed to have a focus on intuitiveness for the everyday user. This means I can map the manager DN to this property and define no filters, and our result will be the user! Search over full text gives users direct access to the words used by the author, rather than being restricted to matching against a document surrogate. Because the number of (English) pages on the Web is so enormous, conjoining query terms is likely to return many results, and because they are more transparent to the user than a weighted term score, conjunction-based queries became the default for Web search. This is not surprising, since asking questions is how we seek information from other people.
An advantage of question answering is that the user can receive a simple, terse answer, such as 30 feet to the question How deep is it safe to dive without worrying about getting the bends? For queries seeking advice or general information about a topic, longer answers were preferred.
After seeing the results, 5 participants could not come up with a meaningful explanation of the results; 6 were close to accurately describing the difference, but 3 required the side-by-side comparison to do so. 9 out of 14 were unable to explain the results in a way that remotely resembled removal of stopwords.
In scanning the bolded query term hits in the document surrogates, some participants noticed the difference in proximity for ranking. Today, search forms often include drop-down menus that show previously issued queries whose prefix matches what has been typed so far (see an example from Microsoft's search in Figure 4.1b). The first showed one empty line and only 18 visible characters (but would accept up to 200 characters) and the second showed 6 lines of 80 characters each, which allowed arbitrarily long queries to be entered.
Dynamic query term suggestions (sometimes referred to as auto-suggest, autosuggest, or search-as-you-type) are a promising intermediate solution between requiring the user to think of terms of interest (and how to spell them) and navigating a long list of term suggestions.
For instance, at eBay, typing in the letter d in the query form shows suggestions such as d oorbusters, d igital cameras}, and d s lite}. The user can select one or more of the suggested terms by double-clicking it, or ignore the suggestions. When comparing time taken and quality of results, there were no significant differences among the systems, although the numbers trended towards the real time query expansion being more effective.
Since modern term suggestion interfaces are much more reactive, this suggests that they are most likely found useful. This, compounded with the fact that the verb ride is a meaningfully related term to space travel, caused some participants to erroneously augment their query with this term.
It is richer than a standard keyword query in that it suggests alternative wordings for each key concept. The disadvantage of exact match of phrases is that it is often the case (in English) that one or a few words fall between the terms of interest (as in big black dog when searching on big dog). For example, Google often ignores middle initials when doing matches against people's names, even when those names are enclosed in double quotes. So given a query consisting of cats dogs fish mice, the system would rank a document with at least one instance of cats, dogs, or fish higher than a document containing 30 occurrences of cats but no occurrences of the other terms. The mandatory operator gave users more control over how the search engine treated their keywords. However, searching over structured information is inherently different than searching over unstructured text.
One participant put quotation marks around almost every individual word, and another, apparently having misunderstood some advice from a friend on how to improve her results, put them around all terms in her query, thus often yielding empty result sets. Most older search systems required special training and expertise, and many users relied on skilled intermediaries such as corporate or university librarians to issue queries.
Titles could be shown by specifying the set number and issuing a command to show the titles. The next command restricts the results to only those whose corporate source contains the terms HARVARD and a name that begins with MEDIC. Many others are noun compounds and proper nouns ( thanksgiving wallpaper, jedi mind tricks, sherlock holmes, and daylight savings time change). On Web sites whose content is divided into different categories, some search engines use a combination of a drop-down menu to select a category of content to search within, alongside the entry form. The authors asked 19 linguistics students to use one of the two interfaces and to find relevant documents for three queries. This process continues with the system suggesting additional terms after each word is entered, until the query is completed (by pressing the Return key). The quality of search results were assessed by two judges, and the precision was found to be higher in the exploratory task for the dynamic term suggestions than for the post-retrieval suggestions, and both were higher than for the baseline. Participants also made positive comments about the post-query suggestions, indicating that they were often helpful when the first query was unsuccessful. Information Processing and Management, 43(3), 2007.">White and Marchionini, 2007 note that if users see search results first, they are less likely to make this kind of mistake. Another consideration is whether or not stemming is performed on the terms included in the phrase. Unfortunately, users sometimes mistakenly thought the + acted as an infix AND rather than a prefix mandatory operator, thus assuming that cat + dog will only retrieve articles containing both terms (where in fact this query requires dog but allows cat to be optional).
Document sets that were not empty could be referred to by a set name and combined with AND operations to produce new sets. The next command requests the system to show the first 10 results from the preceding results set, in format number 3. Less frequently, keyword queries contain syntactic fragments including prepositions ( tots to teens, matron of honor speech) and verbs ( watch pokeman), and in some cases, full syntactic phrases ( history of fish farming in nigeria, construction plans for a trebuchet).
Thus, the idea is similar to dynamic term suggestions, but less interactive, and responsive at the word level only, as opposed to at the character prefix level.
In addition, most query languages that incorporate Boolean operators also require the user to specify rigid syntax for other kinds of connectors and for descriptive metadata. The Google search engine allows a wildcard character operator *, which allows for one or more unspecified words to appear between the two specified words; multiple stars allow for multiple unspecified words. When no results are found for a query such as gap ultra low rise 8r, the searcher is shown a view indicating how many results would be brought back if only k out of n terms were included in the query, as illustrated in Figure 4.8. The need for this operator became obviated after search engines began returning only those documents that contain every keyword.
If this set in turn was too small, the user could back up and try a different combination of sets, and this process was repeated in pursuit of producing a reasonably sized document set.
Most users are not familiar with the use of parentheses for nested evaluation, nor with the notions associated with operator precedence.
In some cases the best solution is to allow users to specify exact phrases but treat them as if they indicated small proximity ranges, with perhaps an exponential fall-off in weight according to the distance between the terms.

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