Method and system for dynamically processing ambiguous, reduced text search queries and highlighting results thereof

Abstract

A method and system are provided of processing a search query entered by a user of a device having a text input interface with overloaded keys. The search query is directed at identifying an item from a set of items. Each of the items has a name including one or more words. The system receives from the user an ambiguous search query directed at identifying a desired item. The search query comprises a prefix substring of at least one word in the name of the desired item. The system dynamically identifies a group of one or more items from the set of items having one or more words in the names thereof matching the search query as the user enters each character of the search query.

Description

BACKGROUND OF THE DISCLOSURE

Field of Invention

The present invention generally relates to processing search queries and, more particularly, to methods and systems for processing ambiguous, reduced text, search queries and highlighting results thereof.

Description of Related Art

There are many user-operated devices such as mobile phones, PDAs (personal digital assistants), and television remote control devices that have small keypads, which a user can use for text entry. In many of these devices, largely because of device size constraints, the keypad is small and has only a small number of keys, which are overloaded with alpha-numeric characters. Text input using these keypads is cumbersome.

FIG. 1 illustrates a common twelve-key keypad interface found in many cell phones and other mobile devices, and also increasingly in devices like television remote control devices. The keypad 10 includes twelve keys 12, most of which are overloaded with multiple alpha-numeric characters or functions. The same key can be pressed to enter different characters. For instance, the “2” key can be used to enter the number “2” and the letters “A”, “B” and “C”. Text entry using such a keypad with overloaded keys can result in an ambiguous text entry, which requires some type of a disambiguation action. For instance, with a so-called multi-press interface, a user can press a particular key multiple times in quick succession to select a desired character (e.g., to choose “B”, the user would press the “2” key twice quickly, and to choose “C”, the user would press the key three times quickly). Alternatively, text entry can be performed using the so-called T9 and other text input mechanisms that provide vocabulary based completion choices for each word entered. Neither of these methods is however particularly suitable for use in performing searches because of the number of steps needed to get to the result. One deficiency of the multi-press interface is that too many key strokes are needed. A drawback of applying a vocabulary based word completion interface is the need for the additional step of making a choice from a list of all possible word matches generated by the ambiguous text input. Furthermore vocabulary based word disambiguation systems are designed typically for composition applications (as opposed to search applications) where user explicitly disambiguates each word by performing a word completion action to resolve that word before proceeding to the next word in the composition. This deficiency is even more apparent for a multi-word search system where results could ideally be obtained by the entry of just a few characters. These methods suffer from the fact that the fewer the number of characters entered, the greater the ambiguity of the input. (The ambiguity decreases as the input character count increases.) This has the undesirable consequence of reducing the usefulness of a search engine that has the potential to retrieve results with just a few input characters.

BRIEF SUMMARY OF EMBODIMENTS OF THE INVENTION

In accordance with one or more embodiments of the invention, a method and system are provided of processing a search query entered by a user of a device having a text input interface with overloaded keys. The search query is directed at identifying an item from a set of items. Each of the items has a name comprising one or more words. The system receives from the user an ambiguous search query directed at identifying a desired item. The search query comprises a prefix substring of at least one word in the name of the desired item. The system dynamically identifies a group of one or more items from the set of items having one or more words in the names thereof matching the search query as the user enters each character of the search query. The system also orders the one or more items of the group in accordance with given criteria. The names of the one or more items of the identified group are output to be displayed on the device operated by the user as ordered with the characters of the one or more words in the names corresponding to the prefix substring of the search query being highlighted.

These and other features will become readily apparent from the following detailed description wherein embodiments of the invention are shown and described by way of illustration. As will be realized, the invention is capable of other and different embodiments and its several details may be capable of modifications in various respects, all without departing from the invention. Accordingly, the drawings and description are to be regarded as illustrative in nature and not in a restrictive or limiting sense with the scope of the application being indicated in the claims.

BRIEF DESCRIPTION OF THE SEVERAL VIEW OF THE DRAWINGS

For a more complete understanding of various embodiments of the present invention, reference is now made to the following descriptions taken in connection with the accompanying drawings in which:

FIG. 1 illustrates a keypad with overloaded keys in accordance with the prior art.

FIG. 2 illustrates a search system in accordance with one or more embodiments of the invention.

FIG. 3 illustrates exemplary device configuration options for various devices for performing searches in accordance with one or more embodiments of the invention.

FIG. 4 is a flow chart illustrating a method for finding and highlighting results of a reduced text, ambiguous search query made using an overloaded keypad in accordance with one or more embodiments of the invention.

FIG. 5A illustrates the different match possibilities for a single-word and multi-word prefix query in accordance with one or more embodiments of the invention.

FIG. 5B illustrates possible ordering criteria for search results in accordance with one or more embodiments of the invention.

FIGS. 6A and 6B illustrate an exemplary text input interface and a display interface, respectively. The display interface shows the results of a sample incremental search where the user has entered a single-word query in accordance with one or more embodiments of the invention.

FIGS. 7A and 7B illustrate an exemplary text input interface and a display interface, respectively. The display interface shows the results of a sample incremental search where the user has entered a multi-word query in accordance with one or more embodiments of the invention.

Like reference numerals generally refer to like elements in the drawings.

DETAILED DESCRIPTION OF THE EMBODIMENTS

Briefly, methods and systems are provided in accordance with various embodiments of the invention for performing searches using ambiguous text input from devices having limited text input interfaces, and highlighting results of the searches.

As described in further detail below, in accordance with various embodiments of the invention, methods and systems are provided for processing a search query entered by a user of a device having a text input interface with overloaded keys. The search query is directed at identifying an item from a set of items. Each of the items has a name comprising one or more words.

Using the text input interface, the user can enter an ambiguous search query directed at identifying a desired item. The search query comprises a prefix substring of at least one word in the name of the desired item. A prefix substring of a word is a variable length string of characters that contains fewer than all the characters making up the word.

The system dynamically identifies a group of one or more items from the set of items having one or more words in the names thereof matching said search query as the user enters each character of said search query. The group of the one or more items is displayed on the device operated by the user with the characters of the one or more words in the names corresponding to the prefix substring of the search query being highlighted. The items are preferably displayed in an order of expected interest to the user.

The user types in the prefix input query by pressing overloaded keys of the text input interface once to form each character of an ambiguous query string. In accordance with one or more embodiments of the invention, the search space containing the searchable items is initially indexed by performing a many-to-many mapping from the alphanumeric space of terms to numeric strings corresponding to the various prefixes of each alphanumeric term constituting the query string. In a numeric string, each alphanumeric character in the string is replaced by its corresponding numeric equivalent based on the arrangement of characters on the keypad, e.g., the commonly used twelve-key reduced keypad shown in FIG. 1. This mapping scheme enables the system in accordance with one or more embodiments to incrementally retrieve results matching the ambiguous alphanumeric input query, as the user types in each character of the query. The user does not have to explicitly specify the termination of each word in the query to assist the system in disambiguating the input query; instead, the user only enters an input query that includes prefix substrings from the one or more words of the query. If multiple word prefixes are entered, the system can leverage off the multiple word prefixes to disambiguate it. A multiple word prefix based disambiguation method can reduce the amount of text and steps needed to enter a multiple word input query and retrieve results.

There are various possible applications for the search techniques described herein including, e.g., assisting television viewers in identifying desired television content items and channels, and assisting users of mobile devices such as cell phones and PDAs in performing searches for items in various databases (e.g., performing searches in directories of people or businesses, searching for and purchasing products/services like airline tickets, and searching for transportation schedules such as airline and train schedules, and for searching for audio and/or video content).

In the context of television systems, the term “television content items” can include a wide variety of video/audio content including, but not limited to, television shows, movies, music videos, or any other identifiable content that can be selected by a television viewer. Searching for television content items can be performed across disparate content sources including, but not limited to, broadcast television, VOD, IPTV, and PVR (local and network).

FIG. 2 schematically illustrates an overall system for performing searches with reduced text entry using various devices in accordance with one or more embodiments of the invention. The system includes a server farm or system 202, a network 204, and a variety of devices 206, 208, 210 operated by users with text input interfaces. In accordance with one or more embodiments of the invention, the server 202 processes search queries received from the user devices 206, 208, 210. In other embodiments, the search queries are processed on the devices themselves. As discussed below, the server 202 can be the source of search data and relevance updates. If part of a television system, the server 202 can also be the source of or be linked to a source of at least some of the available television content (e.g., a cable or satellite television operator) from which the user can obtain content associated with search results.

The network 204 functions as the distribution framework for transmitting data from the server 202 to the devices operated by the users. The distribution network 204 could be wired or wireless connections or some combination thereof. Examples of possible networks include computer networks, cable television networks, satellite television networks, IP-based television networks, mobile communications networks (such as, e.g., wireless CDMA and GSM networks), wired telephone networks, and IP-based wired and wireless networks.

The search devices could have a wide range of interface capabilities. A device, e.g., could be a hand-held mobile communications device 206 such as a cellular phone or PDA having a limited display size and a reduced keypad with overloaded keys. Another type of search device is a television system 204 with a remote control device 208 having an overloaded keypad. Another possible search device is a desk telephone 210 with a reduced keyboard and a small display screen.

FIG. 3 illustrates multiple exemplary configurations for search devices in accordance with various embodiments of the invention. In one configuration, a search device (e.g., devices 206, 208, 210) can have a display 302, a processor 304, volatile memory 306, text input interface 308, remote connectivity 310 to the server 202 through the network 204, and a persistent storage 312. A device configuration for a device such as the hand-held device 206 might not include local persistent storage 312. In this case, the device 206 could have remote connectivity 310 to submit the query to the server 202 and retrieve results from it. Another configuration of the devices 206, 208, 210 may not have remote connectivity 310. In this case, the search database may be locally resident on a local persistent storage 312. The persistent storage 312 may be, e.g., a removable storage element such as SD, SmartMedia, CompactFlash card etc. In a configuration of the device with remote connectivity 310 and persistent storage 312 for performing searches (e.g., a television system 208), the device may use the remote connectivity for search relevance data update or for the case where the search database is distributed on the local storage 312 and on the server 202. A preferred configuration in a memory constrained device is the search data residing remotely on a server. Unlike composition applications where the “most frequently used or popular terms space” are small in size and can be maintained in a local vocabulary, search spaces are typically larger inherently because people instinctively use unique word “signatures” to recall an item of interest. Hence maintaining search spaces locally may not be practical in many devices that have limited local memory, making a network based search configuration preferable.

In one exemplary embodiment, a television system 208 may have a set-top box or other device with a one-way link to a satellite network. In this configuration, all search data including relevance updates may be downloaded to the device through a satellite link to perform local searching. In this case, the set-top box preferably has sufficient storage capacity to maintain search spaces locally. Local storage is preferably large in this case to circumvent the deficiency of a one-way link.

FIG. 4 illustrates a search process in accordance with one or more embodiments of the invention. At step 402, the user enters a character using an ambiguous text input interface, e.g., using a keypad with overloaded keys where a single key press is performed for each character entered. At 404, an incremental search system determines and displays at least some of the results that match the input character entered at 402. Since the input is ambiguous, the match of results would include the matches for all the ambiguous input characters represented by the single key press (including those not of interest to the user). To address this increased set of matches, an ordering scheme is preferably used to order the results to improve accessibility to results expected to be more of interest to the user. The ordering of results can be based on a variety of criteria including, e.g., temporal relevance, location relevance, popularity and personal preferences (that may have been determined implicitly or explicitly) or some combination of these criteria. (In a television application, temporal relevance can be used to favor programs whose timing may be more of interest to the viewer. For example, if the user entered NBA, then the system would list the games in order of temporal relevance such as those in progress or are scheduled to begin in the near future are listed at the higher on the list. The popularity criterion can be used to favor programs or channels that are more popular than others. The personal preference criterion can be used to favor programs or channels that the user has indicated preference for in prior user selections. For example, if a user frequently scrolls down to “CNBC” and selects it, the system would over time place CNBC higher in the list of results over a more generally popular channel such as CNN. Furthermore, identity independent time-based usage pattern learning algorithms can be applied in conjunction with personalization to apply the results ordering rules in an appropriate context. Also, e.g., when using a PDA or cell phone to search for a business, the system may use location relevance as part of the ordering criteria.)

In addition, other ordering schemes can be used in addition to or instead of the schemes indicated above such as character count based subspace biasing. In a character count based subspace biasing scheme, items in the search space do not have a constant relevance value, but rather have a relevance value that is a function of the number of characters entered so far in the prefix substring. In such a scheme, the search space (i.e., set of items that can be searched for) can divided into multiple subspaces. The relative relevance of a given subspace (and all the items contained therein) is dynamically boosted or suppressed as a function of the number of characters in the search query. As an example, a subspace containing television channel names might be boosted when the character count is one because television viewers might expect to find a channel with a single key press. Various examples of character count based subspace biasing are described in U.S. patent application Ser. No. 11/246,432 entitled “Method And System For Incremental Search With Reduced Text Entry Where The Relevance Of Results Is A Dynamically Computed Function Of User Input Search String Character Count” and filed on Oct. 7, 2005, which is assigned to the assignee of the present application and is incorporated by reference herein in its entirety.

The ordering criteria can also give preference to the results matching the search query based on a lexical match of the type of query input, e.g., in the following order of preference: single term prefixes, multiple term prefixes, and lastly abbreviation matches.

In accordance with various embodiments of the invention and as will be described below with reference to FIGS. 6B and 7B, the characters in the search result items that match the search prefix substring characters are highlighted to provide the user with a visual indication of the relationship between the key or keys pressed and the incremental match results. This facilitates identification by the user of the item of interest from the group of items displayed.

If the user does not find the desired results at 406, he or she can continue to enter more characters to the search query at step 402. Then at step 404, the system will perform the search based on the cumulative substring of characters of the search query entered by the user up to that point.

In the scenario where user does not reach the result due to misspelling or due to the case of a word whose uniqueness (e.g., Tom Brown, Todd Brown) is embedded in the suffix of a word in the query (as opposed to the prefix), the user would have to either go back to the first word and enter more characters or erase one or more of the typed characters and re-enter characters to reach the desired result. The dynamic highlight of the prefix strings in the results for each character entry enables the user to recover from an error during the text entry process itself, in contrast to discovering that no results match after typing the entire text.

FIG. 5A illustrates the two broad categories of input queries and the various potential matches they could have in the results space. Input queries that do not include an explicit space or other break character form a single-word prefix query. A single-word query 501 can either match a single-word term 503 or an abbreviation representing multiple words 505. Input queries that explicitly include a space character or other break character between character entries form a multi-word prefix query. A multi-word prefix query 502 can match a multi-word term 504 or an abbreviation presenting multiple words. In an exemplary search of a movie database, the matches could be a direct match on terms representing a title (e.g., for the search query “go mu”, a match could be the movie title Gods Must Be Crazy) or it could be matches on terms representing different types of information (e.g., if a user is searching for a movie starring Tom Hanks that features volleyball, he or she may enter the search query “to vo” to get the result: Tom Hanks Volleyball). As described earlier, these matches are then ordered in decreasing relevance, and in one or more embodiments, in the following order: single-word term matches 506 and multi-word term matches 507 followed by multi-word abbreviation matches 508 as illustrated in FIG. 5B.

FIGS. 6A and 6B illustrate an example of highlighted search results in accordance with one or more embodiments of the invention. FIG. 6A illustrates an overloaded keypad interface 602, which can in a television application, be an on-screen interface. In this example, the user has entered a single-word text input query “866” using the keypad 602. The results of the search input are shown in FIG. 6B, which shows single-word term matches 603 and 604 ordered before abbreviation matches 605 and 606. Because each key pressed by the user is overloaded and represents multiple possible search prefixes, simply displaying the text input “866” with the results will not provide the user sufficient information to associate his or her input with the match results. The “8” character entered initially by the user matches all items in the search database containing any word which begins with any of the alphanumeric characters “8”, “T”, “U” or “V”. Examples of matches to the first character would be “8MM” 604 and “Star Trek” (not shown here since what is shown is the result of the query 866, not 8). The “6” character next entered by the user limits these search results only to items containing words that begin with the alphanumeric characters “8”, “T”, “U” or “V” and whose second character is one of the alphanumeric characters “6”, “M”, “N” or “O” or to items containing words that begin with the alphanumeric characters “8”, “T”, “U” or “V” and that also contain subsequent words that begin with the alphanumeric characters “6”, “M”, “N” or “O”. The earlier match, “Star Trek”, would drop out of the match results when the user pressed the overloaded “6” key because the “r” following the “T” matched by the “8” character does not match “6”, “M”, “N” or “O” and there are no words following “Trek” to match the “6”, “M”, “N” or “O”.

The next “6” character entered by the user as the third overloaded character further limits the search result to only those matches that also contain the alphanumeric characters “6”, “M”, “N” or “O” immediately following one of the matched characters for the first “6” previously entered or that contain subsequent words that begin with the alphanumeric characters “6”, “M”, “N” or “O”. This relationship between the overloaded characters entered by the user and the match results is complicated and not necessarily intuitive to the user. In various embodiments of the invention, the characters in the search result that match the overloaded single-word search prefix characters are highlighted, providing the user with a visual indication of the relationship between the key pressed and the incremental match results. This facilitates identification by the user of the item of interest from the group of items displayed.

The term “highlighting” as used herein refers to making more prominent or otherwise making more distinct characters of interest in the search results relative to other characters. Non-limiting examples of highlighting include bolding, italicizing, coloring, underlining, or changing font of (or some combination thereof) the characters of interest relative to the others.

In another example, FIG. 7B illustrates the results for a multi-word text input “866 2” using a 12-key keypad 702 shown in FIG. 7A. As discussed earlier, the multi-word term matches 703 are preferably ordered ahead of multi-word abbreviation matches. The difference between the single-word search illustrated in FIG. 6B and the multi-word search illustrated in FIG. 7B is that the use of an explicit word separator in the user input (in this case a space character) before the “2” entry, further limits results of the search. Only the results of the search illustrated in FIG. 6B for prefix substring “866” that also contain at least two words and in which a subsequent word begins with “2”, “A”, “B”, or “C” are included in the results displayed to the user. A title such as “Tomb Raider” would not match the multi-word search even though the word “Tomb” matches the overloaded keys “8”, “6”, “6”, “2” because the “2” must match the first letter in a subsequent word. As in the FIG. 6B example, the characters in the ordered result that match the multi-word overloaded search prefix characters are highlighted to provide the user with immediate feedback relating the key pressed to the incremental match results.

Methods of processing ambiguous search query inputs from users and highlighting results in accordance with various embodiments of the invention are preferably implemented in software, and accordingly one of the preferred implementations is as a set of instructions (program code) in a code module resident in the random access memory of a computer. Until required by the computer, the set of instructions may be stored in another computer memory, e.g., in a hard disk drive, or in a removable memory such as an optical disk (for eventual use in a CD ROM) or floppy disk (for eventual use in a floppy disk drive), or downloaded via the Internet or some other computer network. In addition, although the various methods described are conveniently implemented in a general purpose computer selectively activated or reconfigured by software, one of ordinary skill in the art would also recognize that such methods may be carried out in hardware, in firmware, or in more specialized apparatus constructed to perform the specified method steps.

Having described preferred embodiments of the present invention, it should be apparent that modifications can be made without departing from the spirit and scope of the invention.

Method claims set forth below having steps that are numbered or designated by letters should not be considered to be necessarily limited to the particular order in which the steps are recited.

Claims

1. A method, comprising: receiving an ambiguous search input resulting from a plurality of unresolved keystrokes, wherein the unresolved keystrokes correspond to multiple characters resulting in the ambiguous search input;detecting a word separator in the ambiguous search input, the word separator separates a first set of the plurality of unresolved keystrokes from a second set of the plurality of unresolved keystrokes, wherein the first set of unresolved keystrokes is different from the second set of keystrokes;in response to detecting the word separator, identifying a plurality of potential search queries, each potential search query having multiple words, based on the ambiguous search input and the multiple characters corresponding to the unresolved keystrokes, wherein a first word of the words in a first potential search query of the plurality of potential search queries includes a first set of characters that correspond to the first set of unresolved keystrokes and a second word of the words in the first potential search query includes a second set of characters that correspond to the second set of unresolved keystrokes;in response to identifying the plurality of potential search queries: identifying a first content type associated with a first subset of the plurality of potential search queries;in response to identifying the first content type, computing a first content type relevance value of the first content type based on a similarity of the first content type to a characteristic of the ambiguous search input;identifying a second content type associated with a second subset of the plurality of potential search queries;in response to identifying the second content type, computing a second content type relevance value of the second content type based on a similarity of the second content type to the characteristic of the ambiguous search input; andranking the first subset of potential search queries relative to the second subset of potential search queries by comparing the first content type relevance value to the second content type relevance value;determining that a first potential search query in the first subset corresponds to a multi-word term and a second potential search query in the first subset corresponds to a multi-word abbreviation; andgenerating for display the first potential search query and the second potential search query based on the rank of the first subset of potential search queries including presenting the first potential search query before the second potential search query in response to determining that the first potential search query corresponds to the multi-word term and that the second potential search query corresponds to the multi-word abbreviation.

2. The method of claim 1, wherein the characteristic of the ambiguous search input is a number of characters of the ambiguous search input, and wherein the first content type relevance value has a dynamic value which changes in dependence on the number of characters of the search input.

3. The method of claim 1, wherein the characteristic of the ambiguous search input is a number of characters of the ambiguous search input, and wherein the first content type relevance value decreases as the number of characters of the input increases.

4. The method of claim 1, wherein ranking the first potential search query relative to the second potential search query further comprises: comparing a first location relevance of the first potential search query to a second location relevance of the second potential search query.

5. The method of claim 1, wherein the characteristic of the ambiguous search input is whether the ambiguous search input represents the multi-word abbreviation.

6. The method of claim 1, wherein ranking the first potential search query relative to the second potential search query further comprises: comparing a first temporal relevance of the first potential search query to a second temporal relevance of the second potential search query.

7. The method of claim 1, wherein the first content type is TV channels.

8. The method of claim 1, wherein identifying the plurality of potential search queries is performed on a different device from a device on which the unresolved keystrokes are made.

9. A system, comprising: control circuitry;input circuitry configured to receive an ambiguous search input resulting from a plurality of unresolved keystrokes, wherein the unresolved keystrokes correspond to multiple characters resulting in the ambiguous search input; anda memory storing processor-executable instructions, wherein the control circuitry is coupled to the memory and configured to, in response to receiving the ambiguous search input: detect a word separator in the ambiguous search input, the word separator separates a first set of the plurality of unresolved keystrokes from a second set of the plurality of unresolved keystrokes, wherein the first set of unresolved keystrokes is different from the second set of keystrokes;in response to detecting the word separator, identify a plurality of search results, each potential search query having multiple words, based on the ambiguous search input and the multiple characters corresponding to the unresolved keystrokes, wherein a first word of the words in a first potential search query of the plurality of search results includes a first set of characters that correspond to the first set of unresolved keystrokes and a second word of the words in the first potential search query includes a second set of characters that correspond to the second set of unresolved keystrokes;in response to identifying the plurality of search results: identify a first content type associated with a first potential search query of the plurality of search results;in response to identifying the first content type, compute a first content type relevance value of the first content type based on a similarity of the first content type to a characteristic of the ambiguous search input;identify a second content type associated with a second potential search query of the plurality of potential search queries;in response to identifying the second content type, compute a second content type relevance value of the second content type based on a similarity of the second content type to the characteristic of the ambiguous search input; andrank the first subset of potential search queries relative to the second subset of potential search queries by comparing the first content type relevance value to the second content type relevance value;determine that a first potential search query in the first subset corresponds to a multi-word term and a second potential search query in the first subset corresponds to a multi-word abbreviation; andgenerate for display the first potential search query and the second potential search query based on the rank of the first subset of potential search queries including presenting the first potential search query before the second potential search query in response to determining that the first potential search query corresponds to the multi-word term and that the second potential search query corresponds to the multi-word abbreviation.

10. The system of claim 9, wherein the characteristic of the ambiguous search input is a number of characters of the ambiguous search input, and wherein the first content type relevance value has a dynamic value which changes in dependence on the number of characters of the ambiguous search input.

11. The system of claim 9, wherein the characteristic of the ambiguous search input is a number of characters of the ambiguous search input, and wherein the first content type relevance value decreases as the number of characters of the ambiguous search input increases.

12. The system of claim 9, wherein the control circuitry configured to rank the first potential search query relative to the second potential search query is further configured to: compare a first location relevance of the first potential search query to a second location relevance of the second search result.

13. The system of claim 9, wherein the characteristic of the ambiguous search input is whether the ambiguous search input represents the multi-word abbreviation.

14. The system of claim 9, wherein the control circuitry configured to rank the first potential search query relative to the second potential search query is further configured to: compare a first temporal relevance of the first potential search query to a second temporal relevance of the second search result.

15. The system of claim 9, wherein the first content type is TV channels.

16. The system of claim 9, wherein the processor is part of a first device, and wherein the system further comprises a second device comprising a keypad configured to provide the unresolved keystrokes.

17. A non-transitory computer-readable medium having instructions recorded thereon for execution by a processor, the instructions comprising: an instruction for receiving an ambiguous search input resulting from a plurality of unresolved keystrokes, wherein the unresolved keystrokes correspond to multiple characters resulting in the ambiguous search input;an instruction for detecting a word separator in the ambiguous search input, the word separator separates a first set of the plurality of unresolved keystrokes from a second set of the plurality of unresolved keystrokes, wherein the first set of unresolved keystrokes is different from the second set of keystrokes;in response to detecting the word separator, an instruction for identifying a plurality of potential search queries, each having multiple words, based on the ambiguous search input and the multiple characters corresponding to the unresolved keystrokes, wherein a first word of the words in a first potential search query of the plurality of potential search queries includes a first set of characters that correspond to the first set of unresolved keystrokes and a second word of the words in the first potential search query includes a second set of characters that correspond to the second set of unresolved keystrokes; in response to identifying the plurality of potential search queries:an instruction for identifying a first content type associated with a first potential search query of the plurality of potential search queries;in response to identifying the first content type, an instruction for computing a first content type relevance value of the first content type based on a similarity of the first content type to a characteristic of the ambiguous search input;an instruction for identifying a second content type associated with a second potential search query of the plurality of potential search queries;in response to identifying the second content type, an instruction for computing a second content type relevance value of the second content type based on a similarity of the second content type to the characteristic of the ambiguous search input; andan instruction for ranking the first subset of potential search queries relative to the second subset of potential search queries by comparing the first content type relevance value to the second content type relevance value;an instruction for determining that a first potential search query in the first subset corresponds to a multi-word term and a second potential search query in the first subset corresponds to a multi-word abbreviation; andan instruction for generating for display the first potential search query and the second potential search query based on the rank of the first subset of potential search queries including presenting the first potential search query before the second potential search query in response to determining that the first potential search query corresponds to the multi-word term and that the second potential search query corresponds to the multi-word abbreviation.

18. The non-transitory computer-readable medium of claim 17, wherein the characteristic of the ambiguous search input is a number of characters of the ambiguous search input, and wherein the first content type relevance value has a dynamic value which changes in dependence on the number of characters of the ambiguous search input.

19. The non-transitory computer-readable medium of claim 17, wherein the characteristic of the ambiguous search input is a number of characters of the ambiguous search input, and wherein the first content type relevance value decreases as the number of characters of the ambiguous search input increases.

20. The non-transitory computer-readable medium of claim 17, wherein the instruction for ranking the first potential search query relative to the second potential search query further comprises: an instruction for comparing a first location relevance of the first potential search query to a second location relevance of the second potential search query.

21. The non-transitory computer-readable medium of claim 17, wherein the characteristic of the ambiguous search input is whether the ambiguous search input represents the multi-word abbreviation.

22. The non-transitory computer-readable medium of claim 17, wherein the instruction for ranking the first potential search query relative to the second potential search query further comprises: an instruction for comparing a first temporal relevance of the first potential search query to a second temporal relevance of the second search result.

23. The non-transitory computer-readable medium of claim 17, wherein the first content type is TV channels.

24. A method for processing ambiguous search queries, comprising: receiving an ambiguous search input resulting from a plurality of unresolved keystrokes, wherein the unresolved keystrokes correspond to multiple characters resulting in the ambiguous search input;detecting a word separator in the ambiguous search input, the word separator separates a first set of the plurality of unresolved keystrokes from a second set of the plurality of unresolved keystrokes, wherein the first set of unresolved keystrokes is different from the second set of keystrokes;in response to detecting the word separator, comparing the ambiguous search input to words in a search space of associated items to identify a plurality of words matching both a character of the multiple characters and the ambiguous search input, wherein a first word of the words includes a first set of characters that correspond to the first set of unresolved keystrokes and a second word of the words includes a second set of characters that correspond to the second set of unresolved keystrokes;in response to identifying the plurality of words: identifying the first word associated with a first subset of items and the second word associated with a second subset of items from the plurality of words;cross-referencing the first subset of items with a database listing item information to identify a first content type of the first subset of items;cross-referencing the second item with the database listing item information to identify a second content type of the second subset of items;comparing the first content type to the second content type to determine whether the first content type matches the second content type;in response to determining that the first content type does not match the second content type: processing the ambiguous search input to identify a characteristic of the ambiguous search input;computing a first content type relevance value of the first content type by comparing the first content type to the characteristic of the ambiguous search input;computing a second content type relevance value of the second content type by comparing the second content type to the characteristic of the ambiguous search input;ranking the first subset of items relative to the second subset of items by comparing the first content type relevance value of the first item to the second content type relevance value of the second item;determining that a first potential search query in the first subset corresponds to a multi-word term and a second potential search query in the first subset corresponds to a multi-word abbreviation; andgenerating for display the first word associated with the first item and the second word associated with the second item based on the rank of the first subset of items including presenting the first potential search query before the second potential search query in response to determining that the first potential search query corresponds to the multi-word term and that the second potential search query corresponds to the multi-word abbreviation.

25. A system for processing ambiguous search queries, comprising: control circuitry;input circuitry configured to receive an ambiguous search input resulting from a plurality unresolved keystrokes, wherein the unresolved keystrokes correspond to multiple characters resulting in the ambiguous search input; anda memory storing processor-executable instructions, wherein the control circuitry is coupled to the memory and configured to, in response to receiving the ambiguous search input: detect a word separator in the ambiguous search input, the word separator separates a first set of the plurality of unresolved keystrokes from a second set of the plurality of unresolved keystrokes, wherein the first set of unresolved keystrokes is different from the second set of keystrokes;in response to detecting the word separator, compare the ambiguous search input to words in a search space of associated items to identify a plurality of words matching the ambiguous search input, wherein each word of the plurality of words matches a character of the multiple characters, wherein a first word of the words includes a first set of characters that correspond to the first set of unresolved keystrokes and a second word of the words includes a second set of characters that correspond to the second set of unresolved keystrokes;in response to identifying the plurality of words: identify the first word associated with a first subset of items and the second word associated with a second subset of items from the plurality of words;cross-reference the first subset of items with a database listing item information to identify a first content type of the first subset of items;cross-reference the second item with the database listing item information to identify a second content type of the second subset of items;compare the first content type to the second content type to determine whether the first content type matches the second content type;in response to determining that the first content type does not match the second content type: process the ambiguous search input to identify a characteristic of the ambiguous search input;compute a first content type relevance value of the first content type by comparing the first content type to the characteristic of the ambiguous search input;compute a second content type relevance value of the second content type by comparing the second content type to the characteristic of the ambiguous search input;rank the first subset of items relative to the second subset of items by comparing the first content type relevance value of the first item to the second content type relevance value of the second item;determine that a first potential search query in the first subset corresponds to a multi-word term and a second potential search query in the first subset corresponds to a multi-word abbreviation; andgenerate for display the first word associated with the first item and the second word associated with the second item based on the rank of the first subset of items including presenting the first potential search query before the second potential search query in response to determining that the first potential search query corresponds to the multi-word term and that the second potential search query corresponds to the multi-word abbreviation.